Study of Cyclostationarity-Exploiting Algorithms for Emitter Location.

摘要

We have developed, analyzed, and simulated signal processing algorithms to estimate with high resolution the directions of arrival of temporally and spectrally overlapping signals impinging on an antenna array and to estimate the signal waveforms themselves by spatial filtering, with emphasis on algorithms that, by exploiting cyclostationarity, can operate properly when (1) no prior knowledge of the signal, noise, and interference environment is available, except possibly for keying rates or carrier frequencies of signals of interest (these only need be measurable, not know a priori), and (2) physical or economic constraints force the number of deployed antennas in the array to be less than the total number of signals arriving at the array. These two conditions can arise in surveillance, intelligence, and reconnaissance applications when the array size is limited as it is for hand-held or truck-mounted arrays; however, they are typically not addressed by conventional direction-finding and signal extraction methods. For the related problem of estimating time-difference-of-arrival of temporally and spectrally overlapping radio waves impinging on a pair of antennas, typically on separate platforms, for the purpose of passively locating the source of a single in the presence of interfering signals and noise, we have developed, analyzed, and simulated a new class of signal selective algorithms that are highly tolerant to interference and noise. These new algorithms exhibit their signal selectivity regardless of proximity between interfering emitters and emitters of interest. It is only required that the signal of interest have a known or measurable carrier frequency or keying rate that is distinct from those of all interfering signals.