Waveform Diversity and Signal Processing Strategies in Multistatic Radar Systems

2013 ◽  
pp. 286-304
Author(s):  
Bradaric ◽  
Capraro ◽  
Wicks
Keyword(s):  
Signal Processing ◽  
Waveform Diversity ◽  
Radar Systems ◽  
Processing Strategies ◽  
Multistatic Radar

Multistatic Radar Systems Signal Processing

2006 ◽  
Author(s):  
I. Bradaric ◽  
G.T. Capraro ◽  
D.D. Weiner ◽  
M.C. Wicks
Keyword(s):  
Signal Processing ◽  
Radar Systems ◽  
Multistatic Radar

Automotive Radars

2017 ◽  
Author(s):  
Sujeet Patole ◽  
Murat Torlak ◽  
Dan Wang ◽  
Murtaza Ali
Keyword(s):  
Signal Processing ◽  
Pedestrian Detection ◽  
Radar Signal ◽  
Automotive Radar ◽  
Estimation Algorithms ◽  
Radar Systems ◽  
Starting Point ◽  
Processing Techniques ◽  
Automotive Radars ◽  
Signal Processing Techniques

Automotive radars, along with other sensors such as lidar, (which stands for “light detection and ranging”), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to the controller. Automotive radar systems are responsible for the detection of objects and obstacles, their position, and speed relative to the vehicle. The development of signal processing techniques along with progress in the millimeter- wave (mm-wave) semiconductor technology plays a key role in automotive radar systems. Various signal processing techniques have been developed to provide better resolution and estimation performance in all measurement dimensions: range, azimuth-elevation angles, and velocity of the targets surrounding the vehicles. This article summarizes various aspects of automotive radar signal processing techniques, including waveform design, possible radar architectures, estimation algorithms, implementation complexity-resolution trade-off, and adaptive processing for complex environments, as well as unique problems associated with automotive radars such as pedestrian detection. We believe that this review article will combine the several contributions scattered in the literature to serve as a primary starting point to new researchers and to give a bird’s-eye view to the existing research community.

A Power Allocation Approach for 3D Target Tracking in Multistatic Radar Systems

2014 ◽  
Vol 35 (4) ◽  
pp. 901-907
Author(s):  
Jun-kun Yan ◽  
Feng-zhou Dai ◽  
Tong Qin ◽  
Hong-wei Liu ◽  
Zheng Bao
Keyword(s):  
Target Tracking ◽  
Power Allocation ◽  
Radar Systems ◽  
Multistatic Radar ◽  
Allocation Approach

A New Radar Signal Processing Architecture Based on Multi-Core Processor

2014 ◽  
Vol 556-562 ◽  
pp. 1618-1621
Author(s):  
Jia Liang Fan ◽  
Qiang Yang
Keyword(s):  
Signal Processing ◽  
Pulse Compression ◽  
Adaptive Beamforming ◽  
System Structure ◽  
Radar Signal ◽  
Radar Signal Processing ◽  
Test Results ◽  
Radar Systems ◽  
Multi Core Processor ◽  
Processing Architecture

Most radar systems based on the structure that contains many DSP chips. The system structure is always complex, and it is difficult to update. Nowadays, multi-core processor develops very fast. Compared with DSP chips, multi-core processor has better performance in signal processing field. In this paper, we present a signal processing architecture which based on multi-core processor. Pulse compression algorithms and PCI-E bus are discussed as two important technologies. Adaptive beamforming test results show that multi-core processor is able to achieve radar signal processing.

Non‐cooperative target recognition in multistatic radar systems

2014 ◽  
Vol 8 (4) ◽  
pp. 396-405 ◽  
Author(s):  
Pietro Stinco ◽  
Maria S. Greco ◽  
Fulvio Gini ◽  
Mario La Manna
Keyword(s):  
Target Recognition ◽  
Radar Systems ◽  
Multistatic Radar

scholarly journals Rapid jamming avoidance in biosonar

2006 ◽  
Vol 274 (1610) ◽  
pp. 651-660 ◽  
Author(s):  
Erin H Gillam ◽  
Nachum Ulanovsky ◽  
Gary F McCracken
Keyword(s):  
Abrupt Change ◽  
Considerable Effort ◽  
Echolocation Call ◽  
Tadarida Brasiliensis ◽  
Radar Systems ◽  
Spectral Shifts ◽  
Processing Strategies ◽  
Jamming Avoidance ◽  
Sonar Systems ◽  
Behavioural Correlations

The sonar systems of bats and dolphins are in many ways superior to man-made sonar and radar systems, and considerable effort has been devoted to understanding the signal-processing strategies underlying these capabilities. A major feature determining the efficiency of sonar systems is the sensitivity to noise and jamming signals. Previous studies indicated that echolocating bats may adjust their signal structure to avoid jamming (‘jamming avoidance response’; JAR). However, these studies relied on behavioural correlations and not controlled experiments. Here, we provide the first experimental evidence for JAR in bats. We presented bats ( Tadarida brasiliensis ) with ‘playback stimuli’ consisting of recorded echolocation calls at one of six frequencies. The bats exhibited a JAR by shifting their call frequency away from the presented playback frequency. When the approaching bats were challenged by an abrupt change in the playback stimulus, they responded by shifting their call frequencies upwards, away from the playback. Interestingly, even bats initially calling below the playback's frequency shifted their frequencies upwards, ‘jumping’ over the playback frequency. These spectral shifts in the bats' calls occurred often within less than 200 ms, in the first echolocation call emitted after the stimulus switch—suggesting that rapid jamming avoidance is important for the bat.

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