Supercomputer-Aided Space-Time Processing Methods for MIMO Radars in Advanced Airborne Earth Remote Sensing Systems

Vladimir S. Verba; Vyacheslav A. Miheev; Viktor A. Plushchev; Andrei A. Chernienko

doi:10.14529/jsfi260209

Authors

Vladimir S. Verba JSC "Vega Radio Engineering Corporation", Russian Federation https://orcid.org/0009-0002-7633-9556
Vyacheslav A. Miheev JSC "Vega Radio Engineering Corporation", Russian Federation https://orcid.org/0009-0000-2040-8650
Viktor A. Plushchev JSC "Vega Radio Engineering Corporation", Russian Federation https://orcid.org/0009-0003-9411-9386
Andrei A. Chernienko JSC "Vega Radio Engineering Corporation", Russian Federation; JSC "New Start", Russian Federation https://orcid.org/0009-0004-4859-3076

DOI:

https://doi.org/10.14529/jsfi260209

Keywords:

MIMO radar, supercomputer processing methods, reduced-rank algorithms

Abstract

This paper addresses the problem of escalating computational complexity arising from the transition from classical Active Electronically Scanned Arrays to fully-edged Multiple-Input Multiple-Output (MIMO) radars for airborne Earth remote sensing (ERS) systems. It is shown that the formation of a virtual aperture increases the number of virtual channels to 10⁵–10⁶, making classical adaptive processing methods based on direct access to covariance matrices of dimension NN impossible for existing onboard computers. Modifications of the MUSIC and ESBM (Estimation of Signal Parameters via Beamspace Mapping) algorithms have been developed. These algorithms are adapted to operate with sparse covariance matrices, which makes it possible to radically reduce the amount of stored and processed data. Based on the proposed methods, a pipelined processing architecture has been developed and implemented on hybrid CPU+FPGA computers, providing latency compatible with real-time requirements for detection tasks in air-ground and air-sea circuits. The results obtained pave the way for the creation of next-generation airborne radar systems with unprecedented spatial resolution and high noise immunity.

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