The issue of estimation of parameters of radar interference signal has been addressed by algorithms like Grid Search-Maximum Likelihood Estimator (GS-MLE) and principalcomponent Auto-Regressive Estimator (PCar). GS-M...
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ISBN:
(纸本)9781538659069
The issue of estimation of parameters of radar interference signal has been addressed by algorithms like Grid Search-Maximum Likelihood Estimator (GS-MLE) and principalcomponent Auto-Regressive Estimator (PCar). GS-MLE algorithm is an optimal algorithm as it achieves the Cramer-Rao Lower Bound (CRLB) but its time-complexity is high. Another algorithm, that is, the PCaralgorithm is a suboptimal algorithm but it is comparatively faster. In this paper, we propose a hybrid method to further reduce the time-complexity of the PCaralgorithm for large data size (>3000) at both high SNR (>0 dB) and low SNR (<0 dB). However, the estimates of parameters obtained by the Fast PCaralgorithmare reliable only in the SNR range of -20 dB to infinity. This is validated by comparing the Fast PCaralgorithm with the CRLB.
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