Interleaved Low PRF Processing Using Compressed Sensing for Improved Range Estimation in High PRF Pulsed Radars

摘要

Maximum unambiguous range in pulsed radars is a function of transmit inter pulse period(T). For high speed and highly maneuvering targets the inter pulse period has to be sufficiently small to extract intelligible information from radar returns for quick threat analysis and possible target engagement. So a high pulse repetition frequency (HPRF) system is required to work with this class of targets. But HPRF systems have ambiguous range problem which requires complex processing schemes for range extraction. And to utilize the unambiguous range rate information for range extraction we require initial position of the target, which mandates additional communication link with other sensors in the network. On the other hand, low PRF (LPRF) systems have unambiguous range information but very high inter pulse period which is detrimental for tracking high speed targets. In this paper we propose interleaved low PRF processing amidst staggered high PRFs to leverage the benefits of both the schemes. We propose fusion of range unfolding algorithm for staggered high PRFs based on optimized Chinese Remainder Theorem(OCRT) along with compressed sensing(CS) based interleaved low PRF processing for initial range estimation and to provide range reference for correcting estimation errors at periodic intervals. Both the methods run in parallel channels and the output is fused to obtain improved range estimates.