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Tags: analyzer, BRL Test, oscilloscope, test equipment
Low prices on premium quality test equipment is what we are about. Our world class repair lab is what sets us apart.
Tags: 3.5 mm, Network Analyzer Cables, Test Port Return Cables
3.5 mm Flexible Test Port Return Cables – Agilent 85131F On Sale at BRL Test $1,900
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Tags: Advanced Technical Materials, Cree, ETG Canada, High-Power GaN Devices, Ka-band, Mission Microwave Technologies, Passive Components, Sat Com, Solid-State Power Amplifiers, Teledyne Paradise Datacom, Toshiba
Microwaves and RF|
Today’s satcom market can be analyzed by examining five focal points: Ka-band products, GaN devices, solid-state power amplifiers (SSPAs), traveling-wave-tube amplifiers (TWTAs), and passive components.
The latest RF/microwave technology is enhancing performance for the satellite-communications (satcom) industry with a wide range of products. Among the products leading this charge are high-power gallium-nitride (GaN) devices, which are empowering the next generation of solid-state power amplifiers (SSPAs). Because GaN technology can achieve performance levels beyond previous-generation technology, SSPA manufacturers can develop their products with better performance in smaller sizes.
While GaN technology has certainly received a significant amount of attention, traveling-wave-tube (TWT) technology remains a vital aspect of the satcom industry. Ka-band is another major focus, as the usage of this frequency band has significantly increased in recent years. Many Ka-band products are on the market today, as manufacturers seek to support this frequency band. In addition, manufacturers of passive components are supporting the satcom industry with a wide range of products intended for satcom applications. By taking a closer look at these five areas, it is possible to track the near-term evolution of satcom and discover how RF/microwave technology is enabling the satcom industry.
1. Ka-Band Communications
Ka-band is the most recently utilized frequency band to be authorized for commercial satcom. In comparison to other satcom bands, such as Ku-band, Ka-band uses bandwidth more efficiently and is less congested. Thus, Ka-band has become a popular choice for satellite operators in recent years. Although there are some differences worldwide in regards to its exact frequency range, Ka-band is generally considered to span 17.3 to 31.0 GHz. A vast array of RF/microwave products intended for Ka-band satcom applications is available today.
Typical block upconverters (BUCs) used in satellite uplink transmissions convert a band of signals from the L-band frequency range to a higher frequency band, such as C-, Ku-, and Ka-band. The block downconverters (BDCs) that are typically used in satellite downlink transmissions perform the reverse function. They convert a band of signals from a frequency range, such as C-, Ku-, and Ka-band, down to the lower L-band frequency range.
With Ka-band communications becoming more prevalent, high-performance Ka-band BUCs and BDCs are needed to support these requirements. Among the companies offering Ka-band BUCs and BDCs are L3 Narda-MITEQ, GeoSync Microwave, Cross Technologies, Jersey Microwave, and WORK Microwave, to name a few. Some suppliers offer the option to purchase these BUCs/BDCs as either an outdoor unit intended for antenna-mounting or as an indoor unit intended for rack-mounting.
2. High-Power GaN Devices
Today, high-power GaN devices are being used to create the next-generation of GaN-based SSPAs. Prior to the advent of GaN technology, high-power gallium-arsenide (GaAs) devices were widely used to design SSPAs. Thanks to GaN technology’s continuous improvements, SSPA manufacturers are now building SSPAs with GaN devices. GaN technology offers a number of performance benefits in comparison to the older GaAs technology. A GaN device can deliver significantly more power density than a GaAs device. Thus, GaN-based SSPAs can be designed by power-combining fewer devices, resulting in greater efficiency. This also enables GaN-based SSPAs to be built in smaller package sizes than GaAs-based SSPAs. New high-power GaN devices have recently been released, providing additional high-power solutions to the satcom market.
With its portfolio of high-power GaN devices, Cree is one company enabling GaN technology to be utilized in satcom applications. The company recently added to its product line with the release of a new high-power monolithic microwave integrated circuit (MMIC) (Fig. 1). This GaN MMIC is a two-stage high-power amplifier (HPA) intended for Ku-band applications. It is available in a 10-lead, 25-×-9.9-mm, metal/ceramic flanged package (model CMPA1D1E025F) or as bare die (model CMPA1D1E030D).
“Cree’s new Ku-band GaN MMIC HPA was specifically designed in response to customer requests for higher-power and higher-efficiency Ku-band amplifier solutions,” said Tom Dekker, director of sales and marketing, Cree RF. “By delivering higher power, gain, and efficiency at an affordable price point, this amplifier will set the new standard for Ku-band performance.”
Dekker added, “Covering the 13.50-to-14.75-GHz commercial satcom band, the 30-W gallium-nitride-on-silicon-carbide (GaN-on-SiC) MMIC, two-stage high-power amplifier (HPA) enables the satcom industry to achieve higher-power and more efficient Ku-band solutions than the incumbent traveling-wave-tube (TWT) or GaAs solutions used currently. Applications include unmanned intelligence, surveillance, and reconnaissance (ISR), satcom-on-the-move (SOTM) ground vehicles, manned and unmanned aircraft, and maritime vessels.”
High-power GaN devices from Cree are also available for other satcom bands. An example is model CGHV96050F1, which is intended for X-band applications. Ka-band products are also currently being developed.
In addition, Qorvo recently released GaN power amplifiers (PAs) intended for commercial very-small-aperture-terminal (VSAT) and military satcom applications. Those PAs include the TGA2239-CP, TGA2595-CP, and TGA2594-HM. The TGA2239-CP is intended for Ku-band applications, while the TGA2595-CP and TGA2594-HM both target Ka-band applications. The TGA2239-CP provides 35 W output power from 13.4 to 15.5 GHz. The TGA-2595-CP is an 8-W PA covering 27.5 to 31.0 GHz, while the TGA2594-HM provides +36.5 dBm of output power from 27 to 31 GHz. These PAs add to the company’s existing portfolio of high-power GaN products.
For its part, Toshiba has a line of high-power GaN devices that are suitable for C-, X-, and Ku- band applications. A new Ka-band, high-power GaN MMIC is also scheduled to be released by the end of this year. This MMIC, the TGM2931-15, will provide 15 W output power from 29 to 31 GHz. The company also recently began production of the TGI5867-130LH, which is a C-band, 130-W GaN device.
3. Solid-State Power Amplifiers
With the number of high-power GaN devices available on the market, SSPA manufacturers can design their products using the latest GaN technology. Advantech Wireless, for example, has an extensive product line of GaN-based SSPAs. The company offers GaN-based products for C-, X-, DBS-, and Ku-band. As part of the company’s SapphireBlu series, C- and X-band SSPAs with output power levels as high as 6.6 kW are available as well as Ku-band SSPAs with output power levels as high as 3 kW.
One newcomer to the scene is Mission Microwave Technologies. Founded in 2014, the company offers SSPAs with integrated BUCs in a cylindrical package (Fig. 2). The company utilizes advanced GaN transistors, power-combining technology, and novel full-system designs to create compact SSPAs.
“The amplifiers in the new Javelin and Stinger product lines deliver more than 100 W and 55 W at Ku-band, respectively,” said Francis Auricchio, Mission Microwave Technologies’ president and CEO. “Unmatched prime power efficiencies of over 20% are achieved in lightweight, compact form factors that include upconverters, linearization, and integrated power supplies. Both the Stinger and the Javelin amplifiers include a standard user-friendly Bluetooth mobile app remote for monitor-and-control, which makes it simple for users to adjust power levels on the fly without a physical connection to the amplifier. Ruggedized for harsh outdoor environments, our Ku-band amplifiers are available now, with 50-W and 25-W Ka-band amplifiers following right behind.”
Explaining the innovative packaging of these SSPAs, Auricchio noted, “Our unique packaging was developed as we worked to realize the absolute minimum in amplifier size, weight, and volume, which is difficult to achieve by more traditional methods without sacrificing performance and reliability. Typical rectangular-shaped units tend to have heatsinking across the amplifier that is either uniform and underutilized or inefficient and unbalanced. Our cylindrical package optimizes the heatsinking to where it is needed most and provides airflow over the complete amplifier body. These aspects together maintain thermal performance—even in a small form factor. Satcom customers continue to request smaller and lighter units, especially for mobile and man portable applications. By optimizing the form factor of our products, we have been able to deliver this without sacrificing performance.”
A wide range of GaN-based SSPAs also is offered by Teledyne Paradise Datacom. Outdoor SSPAs are available for S-, C-, X-, and Ku-band with a wide range of output power levels. The company provides various packaging options for these SSPAs.
The Outdoor PowerMAX, Teledyne Paradise Datacom’s new high-power SSPA system, was recently unveiled. Its system architecture is a multi-module amplifier system, which allows PowerMAX systems to be configured with a large variety of output power levels. It also is a scalable amplifier system, as an Outdoor PowerMAX system may be initially configured with four modules and later upgraded to eight modules in the field. In addition, the system can grow with future power and bandwidth demands. The C- and X-band versions of the Outdoor PowerMAX system can generate an output power level as high as 10 kW, while the Ku-band version provides as much as 5.7 kW output power.
4. Traveling-Wave-Tube Amplifiers
With the excitement created by GaN technology, it may seem like traveling-wave-tube amplifiers (TWTAs) have been abandoned. However, TWTAs are still being used today. In fact, the technology has advanced in recent years. TWTA manufacturers continue to release new products, demonstrating that this technology is alive and well.
Yet the debate between SSPAs and TWTAs continues. Manufacturers of SSPAs like to point out the advantages that SSPAs have over TWTAs. The introduction of GaN technology has added fuel to the fire, as GaN-based SSPAs can provide performance improvements over previous-generation GaAs-based SSPAs. While SSPAs do have their benefits, TWTAs can still provide advantages over SSPAs in some applications. Thus, deciding on a preferred amplifier technology is dependent on the specific application.
One company providing TWTAs to the satcom market is Tango Wave. The company offers TWTAs for DBS-, Ku-, and Ka-band with output power levels as high as 1250 W (Fig. 3). Those products are designed for direct-to-home (DTH), global up-linking, satellite news gathering (DSNG/SNG), broadcasting, voice/data, mobile up-linking, and maritime applications.
For its part, Comtech Xicom Technology recently introduced the Ku- and DBS-band SuperPower Series TWTAs. These TWTAs are available in both frequency bands as either outdoor antenna-mount units or as indoor rack-mount units. The XTD-2000KHE model is a Ku-band TWTA that provides 750 W of linear output power while drawing less than 3200 W of prime power. The XTD-1500DBSHE model is a DBS-band TWTA that provides 560 W of linear power while drawing only 2500 W of prime power.
The SuperLinear TWTA product line from Communications & Power Industries (CPI) touts advantages in efficiency. These TWTAs range in efficiency from 13% for lower power models to over 22% for 2500-W amplifiers. The company offers SuperLinear TWTAs for X-, Ku-, and Ka-band.
LifeExtender is CPI’s new, patented technology, which is intended to increase a TWT’s lifespan. With the LifeExtender method, a TWT’s lifespan is extended by preserving the active coating on the cathode surface. A TWT reaches the end of its life when its cathode barium reserve is exhausted. The rate of barium evaporation is determined by the cathode temperature, which is in turn determined by the cathode heater voltage setting. With LifeExtender, the cathode heater voltage is adjusted over time to minimize the rate of barium depletion, thereby maximizing the life of the cathode. As a result, a TWT’s lifespan can increase by 30% to 50%.
5. Passive Components
Passive components are an integral part of any satcom system. These components include filters, couplers, isolators, and more. Many manufacturers offer a wide range of passive components for satcom applications.
For example, Advanced Technical Materials (ATM) offers an entire product line of components for Ka-band applications. These components cover the uplink frequency range of 27.5 to 31.0 GHz and the downlink frequency range of 18.3 to 20.2 GHz. The company offers both coaxial and waveguide models. The product line includes power dividers, attenuators, phase shifters, couplers, and more.
Another example of a company providing passive components to the satcom market is ETG Canada. The company’s SSPA original equipment manufacturer (OEM) product line is intended to allow SSPA OEMs to purchase waveguide components from the same vendor. This product line includes adapters, circulators/isolators, terminations, and couplers. The company’s TUBE HPA OEM product line includes many similar components intended for TWTA and klystron power amplifier (KPA) OEMs.
To summarize, a significant amount of activity is occurring in the RF/microwave industry in support of satcom applications. GaN technology is receiving a significant amount of attention, as it is enabling the next-generation of SSPAs. New high-power GaN devices will continue to be released in the near future. TWT technology also continues to be an important contributor to the satcom industry. And as Ka-band satellites continue to be implemented, suppliers are providing components to support this frequency band.
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Tags: Audio Analyzer, HP 8903B, sale
BRL Test – We Absolutely Know Analyzers. Click here for 8903B quote form and data sheet at BRLTest.com.
Agilent 8903B Audio Analyzer
The Keysight/ Agilent/ HP 8903B audio analyzer. Ideally suited for audio measurements from 20 Hz to 100 kHz. The 8903B is an easy to use low-distortion audio source , high-performance distortion analyzer, frequency counter, ac voltmeter, dc voltmeter, and SINAD meter. With microprocessor control of source and analyzer, the 8903B can perform stimulus-response measurements (such as signal-to-noise ratio and swept distortion) automatically with no additional equipment. For ease of use, most measurements on the 8903B are made with only one or two keystrokes. The 8903B automatically tunes and auto ranges for maximum accuracy and resolution. For quick identification of input signals, the analyzer counts and displays the input frequency in all ac measurement modes.
Frequency Range: 50 Hz to 100 kHz
Display Range: 0 to 99.99 dB Accuracy: ±1 dB
Input Voltage Range: 50 mV to 300 V
Residual Noise (the higher of): 80 kHz BW: −85 dB or 17 µV 500 kHz BW: −70 dB or 50 µV
Time to Return First Measurement: <2.5 second
Measurement Rate: One reading per second
Range: 20 Hz to 100 kHz
Accuracy: 0.3% of setting
Range: 0.6 mV to 6 V open circuit
Resolution: 0.3% or better
Accuracy: 2% of setting 60 mV to 6 V, 20 Hz to 50 kHz. 3% of setting 6 mV to 6 V, 20 Hz to 100 kHz. 5% of setting 0.6 mV to 6 mV, 20 kHz to 100 kHz.
Flatness (1 kHz reference): ±0.7% (±0.06 dB), 20 Hz to 20 kHz. ±2.5% (±0.22 dB), 20 Hz to 100 kHz.
Distortion and Noise (the higher of): 80 kHz BW: −80 dB or 15 µV, 20 Hz to 20 kHz. 500 kHz BW: −70 dB or 38 µV, 20 Hz to 50 kHz. −65 dB or 38 µV, 50 kHz to 100 kHz.
Impedance: 600 Ω ±1% or 50 Ω ±2% front panel or HP-IB programmable (47 special function).
Frequency Switching Speed: <3 ms (does not include HP-IB programming time)
Output Level Switching Speed: 20 ms (does not include HP-IB programming time)
Sweep Mode: Log sweep with up to 500 points per decade or 255 points total between entered start and stop frequencies.
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Tags: Antenna Design, Matthew Meiller
Abstract: Wireless device range can be the pivotal make or break characteristic of a successful end product. This paper will dig into the mystery and explore the mechanisms by which wireless range can be reduced or optimized through RF and antenna design. The discussion is relevant to board and system- level circuit and antenna design. The useful rule of thumb that every 1dB of additional RF loss reduces wireless range by 10% is presented.
Index Terms— Wi-Fi, Bluetooth, BLE, Zigbee, RFID, GSM, GPS, MBAN, HBAN, UWB, CDMA, Chip Antenna, Circuit Board Antenna, Wireless Range Reduction, Wireless Range Optimization, Radio Module, 802.11 and 802.15.4
Any RF engineer who has optimized RF or microwave system hardware in the lab will agree that squeezing out the last 1 or 2dB from a design can be the most challenging aspect. After reading this paper you may better appreciate the value of such rigor. This is where the rubber meets the road for applying the art and science of RF design to the development of wireless products. At this point the product requirements may be defined, the theoretical path loss calculations may be complete and you want to ensure execution of the hardware development goes smoothly. Or, the product may be designed and prototypes delivered and debugged, but questions are being asked regarding the wireless range or lack thereof. This article will help the reader understand quantitatively how much wireless range may be lost if the antenna tuning and match steps are neglected, there is more RF loss in the design than anticipated or a related aspect of the design is out of control.
Unintended Loss in the Design
There are many possible sources of insertion loss, mismatch loss and general degradation of antenna gain. These are RF signal losses resulting from product design decisions and features. Collectively we will refer to these as unintended losses and all can have identical impact, which is to reduce the range of wireless products. By referring to them as unintended losses, we mean that they are a consequence of poor RF layout or antenna design and were not factored into the link budget calculation, which can be used early in the design to predict the range of a wireless device.
The RF engineer can prevent these problems and their disastrous consequences by optimizing the performance critical aspects of the design before the prototypes are built, and continuing the optimization and performance assessment in the lab when the hardware is available. This is not a long and drawn out process. It is a matter of simply involving the right expertise with access to the proper design, simulation, and test and measurement tools at the right times. The end result will be a product which provides the best possible wireless performance for your customers and shareholders, with predictable cost and schedule.
Common Sources of Unintended Loss
The contributions from all sources of unintended loss are cumulative, including the separate losses of each of the 2 radios participating in a wireless link. For example, if we have 2dB of mismatch loss and the antenna gain is degraded by 2dB due to the layout, the impact of 4dB must be considered. If two such identical radios are communicating, then the total impact of 8dB must be considered.
Antenna match refers to optimizing the impedance matching network classically located close to the antenna using a piece of test equipment called a RF Vector Network Analyser. The impedance matching network is typically composed of lumped element capacitors and/or inductors, which has values that must be chosen or transmission line stubs which must be trimmed. Once the impedance matching network is tuned based on precision laboratory measurement, subsequent product may be built using the values determined. The purpose of matching the antenna is to force it to resonate over the appropriate range of frequencies for the radio, and to couple as much energy as is possible between the 50 ohm antenna and transmit/receive circuitry.
Circuit Board Layout
If the antenna is mounted on or integrated into a circuit board, careful attention must be given to the layout and the Gerber files reviewed. Often times the antenna used is really only half of the antenna capability since the circuit board RF ground plane plays a key role in the antenna performance. Without the presence of the ground plane and proper control and checking of all the geometric positioning of the antenna and the matching and feed network, the design may be destined to provide poor wireless performance before it is fabricated. The board layout team must be given detailed guidance and instruction, including the positioning of vias critical to RF performance. Simulation tools as well as theoretical knowledge as to how signals behave on circuit boards are needed to get this part of the design right.
Integration of Antenna into Operating Environment
Your end product may use more than one circuit board or contain other large conductive objects such as shielded LAN or USB connectors, transformers or discrete wires and cables. All of these can profoundly impact the performance of your antenna as can proximity to materials such as plastics and conductors. The typical use case should be evaluated, including accessories. Proximity to the human body must be considered if the device is handheld or body worn. Integration of the antenna into the product enclosure refers to evaluating the entire product design with respect to the antenna(s), retuning the impedance matching network in the final assembled product since everything mentioned above can impact antenna performance. Tuning the board used for laboratory development is often different from the final product tuning!
Quantify Impact of Loss on Wireless Range
Free Space Path Loss
Once prototype hardware is built and the wireless link functioning in the lab, the easiest part of the link budget to modify is often the physical separation between the two radios. Technically, we are changing the free space path loss (FSPL). The FSPL gets smaller (less loss) when the radios are moved closer together and vice versa. Here is a handy version of the equation for FSPL:
The distance between the two radios is d (meters), and the frequency of interest is f (Hz).
If we plot path loss vs. separation distanced, the slope of the line is 20dB/decade or 6dB/octave for any range of separation distance d. Figure 1 shows the path loss in dB for 3 different commonly encountered frequencies and a single decade of distance d in meters from 100 to 1000 meters.
Figure 1 • Path Loss Over 1 Decade of Frequency.
Loss Compensation by Range Reduction
If the RF design has unintended loss not accounted for in the link budget, without changing any other variable, we can move the two radios closer together (reduce separation distance d) until they can maintain a wireless radio link. The effect of moving the radios closer together is to compensate for unanticipated loss by reducing the free space path loss defined earlier with an equation. Through inspection of the graph or mathematical analysis of the equation, we determine an approximate rule of thumb that regardless of the source of the loss or separation distance,
Every 1dB of unanticipated loss
Reduces wireless range by 10%!
We are making a linear approximation to quantities plotted on logarithmic scales, and this approximation is reasonably accurate for the final 5dB of link budget power while investigating the maximum separation distance. For example, you expected 300 meter range but your antenna gain is 2dB low, the 2 dB translates into an approximate 20% loss of or wireless range so you measure a range of (300 meters)*(80%)=240 meters. This is a range reduction of 60 meters. If the range is 50% of what you expected, you are compensating for exactly 6dB of unintended loss.
Other Loss Compensation Techniques
Standard coping mechanisms include turning up the transmitter power to compensate for an underperforming RF design. This may appear to work well in the lab, however as we increase transmit power, we also increase the amplitude of spurious emissions and harmonics which often lead to failure when the FCC or ETSI compliance tests are performed. This is similar to stepping on the gas if you have a flat tire. You may move forward for a while, but you will get emissions that you weren’t counting on such as your tire flying apart. If you do not have timely access to RF and antenna engineering capabilities when you need it, Peak Gain Wireless is ready to help with the expertise and equipment to solve these types of problems the right way. We can prevent these problems if we are involved early in the design or define and solve the problem if hardware is already complete.
What does this all mean? Many factors impact the wireless link budget. Examples include antenna selection, design, impedance matching and final product integration. If an antenna has not been properly designed, tuned and optimized in the final product enclosure, it is not uncommon to have a total unintended loss of 2 to 6dB. Since the impact is 10% range reduction per dB loss, this translates into a 20% to 50% range reduction. These types of problems can often be predicted, understood and designed out through EM simulation or the knowledge and insight of an experienced RF engineer with access to the right tools.
About the Author:
Tags: Amplifiers, EMC, Ophir RF
BRL Test is committed to being your one stop shop for EMC equipment. Ophir RF amplifiers have been trusted by the EMC community since 1992. Products range in frequency from 10 kHz to 18 GHz, with power levels from 1 Watt to 24 kilowatts. Made in the USA. Multi year warranties are a testiment to their quality construction and longevity.
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|5063A||Amplifiers||0.8 – 2.0 GHz (200W)|
|5135||Amplifiers||1.0 GHz – 2.0 GHz (300W)|
|5136A||Amplifiers||0.8 – 2.0 GHz (500W)|
|5161||Amplifiers||0.8 – 4.2 GHz (15W)|
|5162||Amplifiers||0.7 – 4.2 GHz (28W)|
|5182||Amplifiers||2.0 GHz – 4.0 GHz (30W)|
|5192||Amplifiers||2.0 GHz – 6.0 GHz (30W)|
|5193||Amplifiers||2.0 GHz – 6.0 GHz (50W)|
|5194||Amplifiers||2.0 GHz – 6.0 GHz (100W)|
|5195||Amplifiers||2.0 GHz – 6.0 GHz (200W)|
|5225||Amplifiers||80MHz – 1GHz (200W)|
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|5285||Amplifiers||2.0 GHz – 4.0 GHz (200W)|
|5293||Amplifiers||1 GHz – 6 GHz (50W)|
|5084||Amplifiers||230.00MHz , 15W|
Tags: 8753ES, Ghz, network analyzer, Price, repair
Can anybody beat this price? If so, email me the quote and we’ll do our best to beat it. Enjoy a 1 year parts and labor warranty that is fully backed by BRL Test’s world classs repair lab. Our techs are the best of the best and we stock a large warehouse of spare parts. We can repair these baby’s fast! Get in for less and limit your downtime risk with BRL Test.
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Tags: 6600, 6610, 6620, 6620A, Krohn-Hite
BRL Test is your sole source for lab standards such as the Krohn- Hite 6620. Call today to lock in on the savings 407-682-4228 or click here for data sheets and quote forms.
The Krone-Hite 6620 provides precision phase measurements with a typical accuracy of 0.02° and a resolution of 0.01° over most of the frequency range. It will accept a wide range of input signal levels from 10mVrms to 320V rms and input waveforms including sine, triangle, square and pulses. A 5 digit LED display provides continuous direct readout of phase angles between 0.00° and 360.00° or ±180°. These two ranges can be manually or automatically selected. The 6620 employs a technique that eliminates phase reading errors usually associated with component drift called Automatic Meter Correct (AMC). AMC provides instant correction of phase readings for zero and full scale errors, making phase measurements more accurate and reliable. The Model 6620 provides a RELATIVE phase measurement mode which allows the monitoring of phase deviations without having to make unwanted calculations. Also provided are an automatic selection of input voltage range, front panel indicators to indicate a too low/high input voltage range, and an analog output for use with an external meter or strip chart recorder. Part No. RK-316 permits the installation of the Model 6620 into a standard 19″ rack spacing.
Tags: 16+4 CH, 500 MHz, 5GS/sec, BRL Test, Mixed signal oscilloscope, sale, Tektronix MSO4054
At BRL Test we’ve been busy buying up oscilloscopes. This means you can save big on premium used, warrantied and certified oscilloscopes. Take the MSO4054. Can anyone beat BRL Test’s price? If so send us your quote so we can beat it.
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As an embedded design engineer, you are faced with the challenge of ever increasing system complexity. A typical embedded design may incorporate various analog signals, high- and lowspeed serial digital communication and microprocessor buses, just to name a few. Serial protocols such as I2C and SPI are used frequently for chip-to-chip communication, but parallel buses are still used in many applications. Microprocessors, FPGAs, Analog-to-Digital Converters (ADCs) and Digital-to-Analog Converters (DACs) are all examples of ICs that present unique measurement challenges in today’s embedded designs. The MSO4000 Series Mixed Signal Oscilloscopes offer the addition of 16 digital channels. These channels are tightly integrated into the oscilloscope’s user interface, simplifying operation and making it possible to solve mixed signal issues more easily. Next Generation Digital Waveform Display In a continued effort to make mixed signal oscilloscopes easy to use, the MSO4000 Series has redefined the way you view digital waveforms. One common problem shared by both logic analyzers and mixed signal oscilloscopes is determining if data is a one or a zero when zoomed in far enough that the digital trace stays flat all the way across the display. The MSO4000 has color-coded the digital traces, displaying ones in green and zeros in blue. The MSO4000 has multiple transition detection hardware. When the system detects multiple transitions, the user will see a white edge on the display. White edges indicate that more information is available by zooming in or acquiring at faster sampling rates. In most cases zooming in will reveal the pulse that was not viewable at the previous settings. If the white edge is still present after zooming in as far as possible, this indicates that increasing your sample rate on the next acquisition will reveal higher frequency information than your previous settings could acquire. Channel setup on an MSO can often be time-consuming as compared to the traditional oscilloscope. This process often includes probing the device-under-test, labeling the channels and positioning the channels on screen. The MSO4000 simplifies this process by allowing the user to group digital waveforms. By simply placing digital waveforms next to each other, they form a group. Once a group is formed, you can position all the channels contained in that group together. This greatly reduces the normal setup time associated with positioning channels individually
Tags: brain surgery, brain-controlled prosthesis, Johns Hopkins University, Nitish V. Thakor
A mesh of electrodes draped over the cortex could be the future of brain-machine interfaces
Last year, an epilepsy patient awaiting brain surgery at the renowned Johns Hopkins Hospital occupied her time with an unusual activity. While doctors and neuroscientists clustered around, she repeatedly reached toward a video screen, which showed a small orange ball on a table. As she extended her hand, a robotic arm across the room also reached forward and grasped the actual orange ball on the actual table. In terms of robotics, this was nothing fancy. What made the accomplishment remarkable was that the woman was controlling the mechanical limb with her brain waves.
The experiment in that Baltimore hospital room demonstrated a new approach in brain-machine interfaces(BMIs), which measure electrical activity from the brain and use the signal to control something. BMIs come in many shapes and sizes, but they all work fundamentally the same way: They detect the tiny voltage changes in the brain that occur when neurons fire to trigger a thought or an action, and they translate those signals into digital information that is conveyed to the machine.
To sense what’s going on in the brain, some systems use electrodes that are simply attached to the scalp to record the electroencephalographic signal. These EEG systems record from broad swaths of the brain, and the signal is hard to decipher. Other BMIs require surgically implanted electrodes that penetrate the cerebral cortex to capture the activity of individual neurons. These invasive systems provide much clearer signals, but they are obviously warranted only in extreme situations where doctors need precise information. The patient in the hospital room that day was demonstrating a third strategy that offers a compromise between those two methods. The gear in her head provided good signal quality at a lower risk by contacting—but not penetrating—the brain tissue.
The patient had a mesh of electrodes inserted beneath her skull and draped over the surface of her brain. These electrodes produced anelectrocorticogram (ECoG), a record of her brain’s activity. The doctors hadn’t placed those electrodes over her cerebral cortex just to experiment with robotic arms and balls, of course. They were trying to address her recurrent epileptic seizures, which hadn’t been quelled by medication. Her physicians were preparing for a last-resort treatment: surgically removing the patch of brain tissue that was causing her seizures.
Seizures result from abnormal patterns of activity in a faulty part of the brain. If doctors can precisely locate the place where those patterns originate, they can remove the responsible brain tissue and bring the seizures under control. To prepare for this woman’s surgery, doctors had cut through her scalp, her skull, and the tough membrane called the dura mater to insert a flexible grid of electrodes on the surface of her brain. By recording the electrical activity those electrodes registered over several days, the neurologists would identify the trouble spot.
The woman went on to have a successful surgery. But before the procedure, science received a valuable bonus: the opportunity to record neural activity while the patient was conscious and under observation. Working with my collaborator at the Johns Hopkins University School of Medicine, Nathan Crone, my team of biomedical engineers has done this about a dozen times in the past few years. These recordings are increasingly being used to probe human brain function and are producing some of the most exciting data in neuroscience.
As a patient moves or speaks under carefully controlled conditions, we record the ECoG signals and learn how the brain encodes intentions and thoughts. Now we are beginning to use those signals to control computers, robots, and prostheses. The woman in the hospital room didn’t need any mind-controlled mechanical devices herself, but she was helping us develop technology that could one day allow paralyzed patients to control robotic limbs of their own.
The machine at the end of a brain-machine interface could be anything: Over the past few decades, researchers have experimented with using neural signals to control a computer cursor, a wheelchair, and even a car. The dream of building a brain-controlled prosthetic limb, however, has received particular attention.
In 2006 the U.S. Defense Advanced Research Projects Agency (DARPA) bankrolled a massive effort to build a cutting-edge prosthetic arm and to control it with brain signals. In the first phase of this Revolutionizing Prosthetics program, the Johns Hopkins Applied Physics Laboratorydeveloped a remarkable piece of machinery called the Modular Prosthetic Limb, which boasts 26 degrees of freedom through its versatile shoulder, elbow, wrist, and fingers.
To give amputees control of the mechanical arm, researchers first tried out existing systems that register the electrical activity in the muscles of the limb stump and transmit those signals to the prosthesis. But such systems offer very limited control, and amputees don’t find them intuitive to use. So DARPA issued its next Revolutionizing Prosthetics challenge in 2009, asking researchers to control the state-of-the-art prosthetic arm directly with signals from the brain.
Several investigators answered that call by using brain implants with penetrating electrodes. At Duke University, in Durham, N.C., and theUniversity of Pittsburgh, researchers had already placed microelectrodes in the brains of monkeys, using the resulting signals to make a robotic arm reachand grasp. Neuroscientists at Brown University, in Providence, R.I., had implanted similar microelectrodes in the cortex of a paralyzed man and showed that he could control a computer cursor using neural signals. Another paralyzed patient who underwent this procedure at Brown recently controlled a robotic arm: She used it to raise a bottle to her lips to take a drink, performing her first independent action in 14 years.
That work certainly demonstrated the feasibility of building a “neural prosthesis.” But using penetrating electrodes poses significant challenges. Scar tissue builds up around the electrodes and can reduce signal quality over time. Also, the hardware, including electrode arrays and low-power transmitters that send the signal out through the skull, must operate reliably for many years. Finally, these first demonstrations did not produce smooth, quick, or dexterous movements. Some neuroscientists suggested that many more electrodes should be implanted—but doing so would heighten the risk of damaging brain tissue.
In light of those concerns, the United States’ National Institutes of Healthchallenged researchers to build a neural prosthesis with a less invasive control mechanism. The ideal would be a system based on EEG signals, simply using electrodes attached to the scalp. Unfortunately, the brain signals that external electrodes pick up are blurred and attenuated by their passage through the skull and scalp. This led our team to investigate the middle road: the use of ECoG signals.
ECoG systems provide a better signal-to-noise ratio than EEG, and the data includes high-frequency components that EEG can’t easily capture. ECoG systems also do a better job of extracting the most useful information from the brain, as an electrode placed over the motor cortex can specifically listen in on the electrical activity most relevant for controlling a prosthetic arm. Similarly, electrodes draped over the brain areas associated with speech can capture signals associated with verbal communication.
Raw ECoG signals appear to be a confused mess of squiggly lines with little discernible pattern. To make sense of the data, our team performs a spectral analysis to deconstruct the signal and find oscillations at certain specific frequencies. These are the brain waves you may have heard about. Neuroscientists have learned that different oscillation frequencies are associated with specific mental states, such as deep sleep, focused attention, or meditative contemplation.
Just imagine what neural prostheses could do for people who are severely paralyzed or for patients in the late stages of amyotrophic lateral sclerosis (also known as Lou Gehrig’s disease). These patients are essentially “locked in,” with intact brains but no ability to control their bodies, or even to speak. Could their intentions, translated into ECoG signals, be captured and relayed to robotic limbs?
Here’s a simple example of how an ECoG-based neural prosthesis could work. Researchers have previously shown that an imagined movement modulates the brain’s electrical activity in the mu band, which has a frequency of about 10 to 13 hertz. Thus, the paralyzed subject would imagine moving a limb, electrodes would capture the mu-band activity, and the BMI would use the signal to trigger an action, such as closing a robotic hand. Since we can use up to 64 electrodes placed about a centimeter apart and spread over a wide area of the brain, we have a lot of data to work with. As we develop better algorithms that can identify the key signals that code for movement, we can build systems that don’t just trigger an action but offer more fine-tuned control.
Our team took the first step toward building such a system in 2011, when we painstakingly matched up brain signals with particular movements. Our subject was a 12-year-old boy awaiting surgery for his seizure disorder. In the experiment, the boy reached forward and grasped one of the wooden blocks set before him, then released it and withdrew his hand. When we looked at the data from just a few electrodes that had been placed over his brain’s sensorimotor cortex, we discovered that oscillations in the high gamma band, with frequencies between 70 and 150 Hz, correlated well with the boy’s actions. We also found that the signal in a lower frequency band changed in predictable ways when he wiggled his fingers.
The next step was to couple the electrical signal to the machinery. We demonstrated that under carefully controlled conditions, epileptic patients with ECoG electrodes placed on their brains could indeed command the Modular Prosthetic Limb to perform simple actions, like reaching and grasping. While this was a considerable accomplishment, we struggled to decode the neural signals reliably and to get the prosthetic limb to move smoothly.
In the end, we decided that it just may not be realistic to expect an ECoG-controlled prosthesis to perform an entirely natural limb movement, such as picking up a pot of coffee and pouring some into a cup. After all, a typical person uses a combination of vision, touch, motor control, and cognitive processing to perform this mundane action. So last year our team began exploring another strategy. We built a hybrid BMI that combines brain signals with input from other sensors to help accomplish the task at hand.
Several epileptic volunteers with ECoG arrays tested our novel system. The first, the woman described at the beginning of this article, focused her eyes on the image of a ball on a computer screen; the computer was streaming video from a setup across the room. An eye-tracking system recorded the direction of her gaze to locate the object she wanted to manipulate. Then, as she reached toward the screen, her ECoG electrodes recorded neural signals associated with that action. All this information was relayed to a robotic arm across the room, which was equipped with a Microsoft Kinect to help it recognize objects in three-dimensional space. When the arm received the signal to reach for the ball, its path-planning software calculated the necessary movements, orientations, and grasp configuration to smoothly pick up the ball and drop it in a trash can. The results were encouraging: In 20 out of 28 trials, this woman’s brain signals successfully triggered the robotic arm, which then completed the entire task.
Would this patient have done even better if we’d implanted electrodes in her brain rather than just draping the electrodes over the surface? Perhaps, but at a greater risk of brain trauma. Also, penetrating electrodes register only the local activity of individual cells or small clusters of neurons, whereas ECoG electrodes pick up activity across broader zones. ECoG systems may therefore be able to capture a richer picture of the brain activity taking place during the planning and execution of an action.
ECoG systems also hold the promise of being able to convey both motor and sensory signals. If a prosthetic limb has sensors that register when it touches an object, it could in principle send that sensory feedback to a patient by stimulating the brain through the ECoG electrodes. Similar stimulation is already done routinely in patients prior to epilepsy surgery in order to map the brain regions responsible for sensation. However, the sensations elicited have typically been very crude. In the future, more refined brain stimulation, using smaller electrodes and more precise activation patterns, may be able to better simulate tactile feedback. The goal is to use two-way communication between brain and prosthesis to help a user deftly control the limb.
While it might be tempting to test ECoG systems with severely paralyzed patients—the intended beneficiaries of this neuroprosthetic research—it is imperative to demonstrate that such systems can reliably restore meaningful function before exposing patients to the risks of surgery. For this reason, the clinical circumstances of patients preparing for epilepsy surgery represent an important opportunity to develop technology that will benefit a very different group of patients. We’ve found that many epilepsy patients are glad they can help others while they’re hospital-bound and under observation for the seizures that will provide guidance to their surgeons. Our hope is that these experiments will lead to a technology so clearly useful that we will feel well justified in trying it in paralyzed patients.
Thinking about the cost-benefit concerns gives a sense of déjà vu. I came to Johns Hopkins in the early 1980s, when doctors there had just implanted the first heart defibrillator in a patient. All the same doubts were aired. Was the technology too invasive? Would it be reliable? Would it provide enough benefit to justify the expense? But defibrillators rapidly proved their worth, and today more than 100,000 are implanted every year in the United States alone. The medical community may be nearing the same juncture with brain-machine interfaces, which might well be an accepted part of clinical medicine in just a couple of decades.
So far I’ve discussed the possibility of using ECoG signals to control prosthetic limbs, but there’s another fascinating possibility: Capturing these signals could also help people who have lost the ability to speak. For some people who have suffered a stroke or injury, the brain can still conceive words and generate speech commands, but the signals don’t make it to the mouth. When ECoG electrodes are placed over the language areas of the brain, including the regions that govern the muscles of speech articulation, the resulting signals presumably carry information pertaining to both language generation and the physical production of words. A speech prosthesis could decode those signals and send commands to a device that would give voice to the patient’s intended sentences.
Early research shows progress in understanding the brain’s commands to the mouth muscles. In one study, University of California researchers in San Francisco and Berkeley used an ECoG system to record activity in the motor cortex as their subjects patiently recited syllables such as “ba,” “da,” and “ga.” The resulting measurements showed distinct patterns for different consonants. For example, certain electrodes showed activity during the production of the “b” sound, which requires closure of the lips. Other electrodes registered activity during the “d” sound, in which the tongue hits the roof of the mouth. Still others saw action during the “g” sound, which involves the back of the mouth.
What would it take to build a speech prosthesis? First, we would need to improve our recording hardware. Today’s ECoG systems use only a few dozen electrodes on the cortex; clearly, a much higher density of electrodes would produce a better signal. We have already tried out new microelectrode ECoG systems in human patients that can pack 16 electrodes onto a 9-by-9-millimeter array.
Because speech production surely involves many brain regions, we’ll also have to improve our signal analysis to decipher neural activity, not just in one area but across large regions of the brain. We’ll need better spatial and temporal resolution to determine the exact sequence in which groups of neurons across the cortex fire to produce, say, the simple sound “ba.” Once we’ve managed to map individual phonemes or syllables, we can work toward understanding fluid speech by decoding a succession of brain commands.
Controlling a robot with a thought, speaking without making a sound: With ECoG systems, these magical feats now appear well within the realm of feasibility. By casting a net of electrodes over the surface of the brain, it’s possible to capture echoes of the ideas and commands that swirl below, in the currents of the mind.
This article originally appeared in print as “Catching Brain Waves in a Net.”
About the Author
Nitish V. Thakor, director of the Laboratory for Neuroengineering at Johns Hopkins University, embraces the fundamental scientific challenge of mapping electrical activity in the human brain. But what gets him out of bed in the morning, he says, are the clinical applications. He hopes the brain-machine interfaces he’s developing in collaboration with colleagues at the Hopkins School of Medicine will one day let paralyzed patients control robotic limbs with their brainwaves.