Monopulse radar detection and localization of multiple targets via joint multiple-bin processing

If several closely-spaced targets fall between two matched filter samples in range, monopulse information from both of these samples can and should be used for estimation, both of angle and of range (i.e., estimation of the range to sub-bin accuracy). Here, a model is established and a maximum likelihood (ML) extractor is developed. A limit of the number of targets that can be estimated is established, and indeed it will be shown that the new extractor can detect up to five targets in a range extent of one resolution cell, meaning from detections in two adjacent matched filter samples. A minimum description length (MDL) criterion is used to detect the number of targets between the two matched filter samples. Simulations are presented to show the performance of the new extractor.