Title :
Analyzing space-time adaptive processors using measured data
Author :
Himed, Braham ; Melvin, William L.
Author_Institution :
Res. Assoc. for Defense Conversion Inc., Marcy, NY, USA
Abstract :
We use monostatic data obtained from the Multichannel Airborne Radar Measurements (MCARM) program to conduct a comparative analysis of various space-time adaptive processing techniques. Specifically, we consider reduced-dimension and reduced-rank methods. The measured data analysis shows the significance of training sample selection, effects of nonhomogeneity in the clutter data, sensitivity of certain classes of adaptive filters to the rank of the measured clutter signal and suitability of the various approaches.
Keywords :
adaptive filters; adaptive radar; adaptive signal processing; airborne radar; covariance matrices; data analysis; filtering theory; radar applications; radar clutter; radar signal processing; search radar; Multichannel Airborne Radar Measurements program; adaptive filters; airborne surveillance radar; clutter data nonhomogeneity; interference covariance matrix; measured clutter signal; measured data analysis; monostatic data; multidimensional adaptive filtering; radar cross-section; reduced-dimension methods; reduced-rank methods; space-time adaptive processing; space-time adaptive processors; training sample selection; Adaptive filters; Airborne radar; Clutter; Covariance matrix; Force measurement; Interference; Maximum likelihood estimation; Radar cross section; Sensor arrays; Vectors;
Conference_Titel :
Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-8316-3
DOI :
10.1109/ACSSC.1997.680579
