Mono-pulse radar angle estimation algorithm under low signal-to-noise ratio

Abstract

Abstract In the case of low signal-to-noise ratio (SNR), in order to improve the angle measurement accuracy of the mono-pulse radar seeker, a target angle estimation algorithm is proposed. The algorithm takes the target angle as a state variable under the Bayesian framework, expands it to the state vector, performs state modeling and observation modeling on it, and builds a particle-based eye angle estimator, which improves the target angle estimation performance. The effectiveness of the algorithm is verified by the simulation data of the medium pulse repetition frequency radar seeker.