Weight Matrix-Based Least Mean Square Algorithm for Target Detection in Passive Radars

Ambiguity function analysis is the most expensive process for target detection in passive radars. The computational cost is attributed to the extensive range-Doppler field required to evaluate the cross-correlation function. Some tools like fast Fourier transform or batching algorithm are employed to partially reduce the computational effort. In this paper a different generalization of least mean square algorithm is utilized for target detection. The basic idea is to employ the properties of the computed weight matrix to extract target coordinates. The algorithm performance is investigated by computer simulation using some practical simulated FM stereo signal. The results reveal the lower computational complexity of the presented procedure compared to existing methods..