We present an efficient algorithm for high resolution time delay estimation in colored Gausslan nalse with multiple looks. By using a relaxation-based optimization approach and exploiting the Toeplitz property of the noise eovaliauee matrix, the enhaneed new algorithm can achieve the corresponding Cramer-Rao bounds (CRBs) with a very small number of lndependent looks.

In sonar and many other applications, time-delay estimation is an important problem. When bandpass probe signals are used, the correlation function between the received and the known transmitted signals oscillates near the carrier frequency of the transmitted signal. In this case, many existing time-delay estimation algorithms perform poorly due to converging to local optimum points. In this paper, two efficient algorithms, Hybrid-WRELAX and EXIP-WRELAX, are proposed to deal with the above problem. They are relaxation-based global minimizers of a highly oscillatory nonlinear least-squares cost function. Both algorithms are shown to achieve the Cram´er–Rao bound and require only a sequence of weighted Fourier transforms.

It is demonstrated through simulations that a combination of the vector auto-regressive (VAR) filtering technique and a maximum likelihood (ML) parameter estimation method is an effective means for carrying out clutter suppression and parameter estimation, and being more robust against system mismatches than conventional displaced-phase-centre-antenna (DPCA) processing.

APES (Amplitude and Phase EStimationl is an adaptive FIR filtering approach introduced recently for complex spectral estimation. For stationary signals, APES can yield more accurate spectral estimates than the widely used Capon and FFT estimators. The authors present a recursive APES algorithm for time-varying spectral analysis, which is computationaly efficient and only involves FFT and simple matrix operations. The recursive APES algorithm is applied to ISAR (inverse synthetic aperture radar) imaging and feature extraction of targets with complex manoeuvring motion. Both numerical and experimental examples are provided to demonstrate the performance of the proposed method.