Answers are grounded in this paper and cite their sources.
Finds a method for resolving closely spaced signals in parameter space, suggesting improved detection efficiency.
This paper presents a method for resolving signals closely spaced in parameter space in the sense that the parameters of the signals being measured (i.e., time of arrival, frequency, etc.) are close together. A maximum-likelihood method is used to resolveMsignals inK-dimensional space, whereMmay be unknown. The resulting procedure first generates aK-dimensional cross-ambiguity function and then passes this function through aK-dimensional linear filter. The procedure effectively reduces the problem from its original form of optimally searching for a maximum in the(M × K)-dimensional space to searching forMmaxima in theK-dimensional parameter space. The method is obviously sub-optimal; its advantage lies in the relatively simple form of the detection scheme.
No takes yet. Share an insight, caveat, or question.
Lichtenstein et al. (1968) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: