Study on STAP Algorithm for Radar Target Detection in Heterogeneous Environments

In heterogeneous environments, due to the lack of the independently and identically distributed (IID) samples, the performance of traditional STAP is degraded severely. The maximum likelihood amplitude and phase estimation of a sinusoid (APES) algorithm can operate directly on data of range cell-under-test. However, this algorithm is based on space domain adaptive processing, which is insensitive to weak target, and mistaking the interference as the true target for the identical Doppler frequency. In this paper, an improved algorithm is proposed, which applies space-time two-dimension APES algorithm to estimate the target’s amplitude, then detecting the moving target according to the output signal-to-noise ration, overcoming the original algorithm’s shortcoming effectively. Simulation results are presented to demonstrate the validity of this improved method.