Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
GLRT-based adaptive detection algorithms for range-spread targets
IEEE Transactions on Signal Processing
Adaptive detection of range distributed targets
IEEE Transactions on Signal Processing
Adaptive array detection of uncertain rank one waveforms
IEEE Transactions on Signal Processing
Hi-index | 0.02 |
This paper presents a unified framework, based on the generalized likelihood (GL), for the detection of targets and the estimation of their direction of arrival (DoA), when operating with modern radar systems that have general antenna array configurations, which contain a mixture of high- and low-gain beams. Adaptive processing structures are presented to remove both side lobe and main lobe electromagnetic interference and intrinsically perform waveform compression when coded radar waveforms are transmitted. Moreover, the processing schemes derived from the GL are decomposed into a cascade of basic processing steps. This can be directly related to the structure of conventional radar schemes, where each processing block is properly optimized. The detection performance is studied by closed form expressions, that show the intrinsic CFAR properties of the considered generalized likelihood ratio test. Then the target DoA estimation accuracy is quantified by the Cramer Rao lower bound. Finally, detection and estimation results are combined to determine practical array configurations that give high overall performance.