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In modern radar signal processing the Space-Time Adaptive (STAP) filtering establishes a significant part of statistical signal processing. Whenever there is requirement to process signals that result from operation in an environment of unknown statistics, the use of an adaptive filter offers an attractive solution to the problem as it usually provides a significant improvement in performance over the use of a fixed filter designed by conventional methods. In this paper we study the use of three different adapting algorithms for adaptive generalized sidelobe canceler of interference signal suppression which intercepted by a uniform linear phased array antenna. Results are plotted, discussed and compared to each other. The paper is divided into four main sections. The problem is defined in the introduction section. In the next section, the adaptive spatial-temporal processor is depicted as well the autocorrelation matrix R has been driven. Next, the filtering using the normalized least mean-square (NLMS) algorithm was discussed. Also, we study the use of normalized fractionally low-order moment algorithm (NFLOM) for adapting of the same uniform linear array antenna and it was explained in section 6. It was compared to the NLMS algorithm for rate of convergenc, minimum mean-square error and angular –doppler beam pattern. In the last section, The recursive least-square (RLS) algorithm was implemented to get the adaptive filtering weight vector and compared to previouse algorithms. Finally, we’ve concluded all the results discussed in each algorithm.

A Performance Evaluation of Signal Filtering with different Adaptive Algorithms on Doppler-Angular Adaptive Generalized Sidelobe Canceler (GSC)