Radar-based detection using angle of arrival estimation based on pruned sparse learning of support vector

Abstract

In various examples, a radar system includes a logic circuit with a memory array for processing radar reflection signals. In a specific example, a method includes generating output data indicative of the reflection signals' amplitudes, and discerning angle-of-arrival information for the output data for the output data by correlating the output data with an iteratively-refined estimate of a sparse spectrum support vector ('support vector'). The estimate includes: iteratively updating a set of parameters associated with previous values of the support vector including a covariance estimate, and a statistical expectation among a plurality of support vectors; and pruning, for each iterative update, certain of the plurality of support vectors having amplitudes which are insignificant relative to the statistical expectation of the support vector of in a preceding iteration.