Title
Design and analysis of compressed sensing radar detectors
Author
Anitori, L.
Maleki, A.
Otten, M.P.G.
Baraniuk, R.G.
Hoogeboom, P.
Publication year
2013
Abstract
We consider the problem of target detection from a set of Compressed Sensing (CS) radar measurements corrupted by additive white Gaussian noise. We propose two novel architectures and compare their performance by means of Receiver Operating Characteristic (ROC) curves. Using asymptotic arguments and the Complex Approximate Message Passing (CAMP) algorithm, we characterize the statistics of the l1-norm reconstruction error and derive closed form expressions for both the detection and false alarm probabilities of both schemes. Of the two architectures, we demonstrate that the best performing one consists of a reconstruction stage based on CAMP followed by a detector. This architecture, which outperforms the l1-based detector in the ideal case of known background noise, can also be made fully adaptive by combining it with a conventional Constant False Alarm Rate (CFAR) processor. Using the state evolution framework of CAMP, we also derive Signal to Noise Ratio (SNR) maps that, together with the ROC curves, can be used to design a CS-based CFAR radar detector. Our theoretical findings are confirmed by means of both Monte Carlo simulations and experimental results. © 2012 IEEE.
Subject
Physics & Electronics
RT - Radar Technology
TS - Technical Sciences
Defence Research
Radar
Defence, Safety and Security
Target detection
Compressed sensing
Detection probability
False alarm probability
Radar
Error statistics
Monte Carlo methods
Radar measurement
Signal reconstruction
Signal to noise ratio
Computer architecture
To reference this document use:
http://resolver.tudelft.nl/uuid:7422c2f1-25ba-402e-bf52-0bc513723f66
DOI
https://doi.org/10.1109/tsp.2012.2225057
TNO identifier
471489
Source
IEEE Transactions on Signal Processing, 61 (4), 813-827
Document type
article