In this article, two recursive algorithms for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived. They are based on a maximum likelihood… Click to show full abstract
In this article, two recursive algorithms for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived. They are based on a maximum likelihood approach and combine an innovative single-tone estimator with a serial cancellation procedure. Our numerical results lead to the conclusion that the developed methods can achieve a substantially better accuracy–complexity tradeoff than various related techniques in the presence of multiple closely spaced tones. Moreover, they can be exploited to detect multiple closely spaced targets and estimate their spatial coordinates in multiple-input multiple-output frequency-modulated continuous wave radar systems.
               
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