Market research firm Markets and Markets expects the radar systems market to grow from USD 20.29 billion in 2016 to USD 26.37 billion by 2021, at a CAGR of 5.39% from 2016 to 2021. According to the firm, factors, such as increased usage of radar systems in unmanned vehicles and homeland security, are expected to drive the growth of the radar systems market.
The report notes that the commercial segment is expected to lead the radar systems market, which can be mainly attributed to the increasing demand for radars across various industries, such as automotive and oil and gas.
Solid-state an enabling technology
One of the key drivers in the radar market is the rising use of GaN solid state power amplifiers, which are achieving higher power levels and wider bandwidths than before. Solid-state devices offer many advantages over older radar technology, such as lighter weight, smaller size, instant turn on, wide band capabilities leading to higher resolution, high efficiency, and low power operation. Solid-state radar also enables designers to implement phase-array systems that have no moving parts and that enable radar signal to be digitised, with a host of signal processing benefits from target recognition to adaptive and cognitive systems.
Higher power, and higher frequency power transistors enable more and more applications to be addressed with solid-state radar.
To illustrate the abilities of GaN-on-SiC, which is a higher power process then GaN-on-Si, Wolfspeed, a Cree Company, recently completed a lineup of GaN-on-SiC high efficiency, high gain, and wide bandwidth C-band radar parts with the introduction of the CGHV59070 GaN HEMT for C-band radar systems.
“First demonstrated at this year’s International Microwave Symposium, the market release of the 70-W CGHV59070 pre-driver completes Wolfspeed’s C-band radar lineup of pre-drivers, drivers, and output stages, enabling 1 kW, all-GaN SSPAs for C-band radar applications,” said Jim Milligan, RF and microwave director, Wolfspeed. “This latest introduction also further extends our comprehensive radar product portfolio, which helps designers achieve smaller, lighter, and higher power RF amplifiers that are critical for the development of the next-generation military, aerospace, and commercial radar applications.”
On the cost side, Ampleon use LDMOS to target lower power radar applications, though the company also have GaN for radar as well. Ampleon offer two 400-W S-band power amplifier pallets designed for a variety of civil and military radar applications. These small form factor modules, measuring just 55- x 35-mm, reduce the overall size of the PA sub assembly in addition to reducing the BOM cost of the design.
Optimised for SWaP-CR (size, weight and power – cost and reliability) constraints, these 9th generation 32-V LDMOS technology pallets meet the industry requirements of cost and reliable performance. ITAR-free, the BLS9G3135P-400 and BLS9G2934P-400 are 50 Ohm matched modules that help engineers create high power systems. The BLS9G2934P-400 has an output power >400 W, a gain of >10 dB, an efficiency >40%, and can operate in the range 2.9 to 3.4 GHz. Production quantities are expected to be available in Q4, 2016.
GaN RF power transistors based on a 0.5 µm HEMT process technology from Ampleon comprise 10 W, 30 W, 50 W and 100 W devices that are suitable for multiple applications such as drivers up to C band, through to 100 W and 200 W push-pull packages for use in final stages up to S band. Housed in a compact and thermally stable ceramic package, the whole CLF1G family of devices are ideal for use in a broad range of applications that need to meet specific requirements of SWaP (size, weight and power).
Adaptive and cognitive radar
As military systems get more complex with the trend to adaptive and cognitive radar, signal processing in the digital domain is becoming even more challenging. Such radar systems might be jammed and adaptive radar that can work around jamming signals adds to the overall effectiveness of the system. Consequently, radar is moving from fixed analog systems to programmable digital systems that are agile and can adapt their behaviour to their environment. In turn, as battlefield capabilities evolve and radar becomes smarter, EW systems need to be able to rapidly characterise emerging radar threats, implement electronic countermeasures, and assess the effectiveness of the response.
In the USA, DARPA are running the Adaptive Radar Countermeasures (ARC) program, which aims to enable airborne EW systems to automatically generate effective countermeasures against new, unknown and adaptive radars in real-time in the field.
According to DARPA, ARC technology will enable radar systems to:
- Isolate unknown radar signals in the presence of other hostile, friendly and neutral signals.
- Deduce the threat posed by that radar.
- Synthesize and transmit countermeasure signals to achieve a desired effect on the threat radar.
- Assess the effectiveness of countermeasures based on over-the-air observable threat behaviors.
One company actively involved in this program, BAE Systems, contends that final implementation of the ARC program is projected to occur by 2018, with demonstrations through live flight tests on an existing EW system. As part of ARC Phase 2, BAE Systems will deliver a prototype system that will feature software algorithms capable of detecting and countering emerging radar threats, providing a major capability enhancement without the need for costly hardware upgrades.
On the automotive side, complex environments involving many slow moving objects need to be detected, especially at close proximities and at a resolution that enables the target to be identified by software algorithms. The challenge here is to be able to identify targets that need to be avoided faster than a human driver is capable of achieving – implying the need for compute intensive signal processing for advanced driving aids and eventually an AI system on wheels for future autonomous vehicles.
Automotive radar to drive a new market
Radar promises to be a major contender for autonomous cars due to its ability to measure the velocity, range and angle of objects. Radar requires less processing power than a camera and uses much less data than Lidar. It can also work in every weather and lighting condition as well as use reflection to see behind obstacles. Cameras and Lidar also have advantages — Lidar can generate precise 3D maps of its surroundings, while cameras are ideal for scene interpretation. It is expected that all three will play an important role in autonomous driving. Radar is already in the market for applications such as forward collision warning systems and adaptive cruise control.
According to market research firm, Wise Guy Reports, the global automotive radar market accounted for $1.2 billion in 2015 and is expected to reach $3.9 billion by 2022 growing at a CAGR of 18.7% from 2015 to 2022. The market is being driven by increasing advancements in design and functionality of products, growing use of parking and collision sensors and higher demand for self driving features.
Though the majority of automotive radar applications are expected to centre around 77 and 79 GHz, other frequencies are being looked at. It should be noted that the 24 GHz band in the EU is temporary for automotive radar use as it faces issues with interference. It is used by radio astronomy stations and the band will be closed before usage becomes too dense.
Already working with automotive radar market leader Infineon Technologies AG at 79 GHz in 28nm CMOS, the IMEC research institute (Heverlee, Belgium) is looking at yet a smaller wavelength to add machine learning to the back end of its sensors.
According to Wim van Thillo, program director for perceptive systems at IMEC, his group is already working on a 140 GHz chip. At this frequency the wavelength is 2.2 mm. IMEC is aiming for more than 4 GHz of bandwidth from a chip measuring 1 square millimeter.
Advantages will include higher distance and angular resolution at lower power in a much smaller system size with the radar able to include the antenna-on-chip. In addition to angle and distance, the radar is able to provide speed information via a mini-doppler effect. The use of multiple antennas integrated on to the chip will result in enhanced Doppler resolution and a better depth resolution.
The signal processing that will be needed to extract speed information is likely to be taken further with the use of algorithms for pattern recognition and automatic learning. As a result Van Thillo envisages a time when the radar will be able to recognize and distinguish the signature of pedestrians, bicycles and cars from their mini-Doppler signatures.
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