Abstract
The ACM-ML (Amplitude comparison monopulse-Maximum Likelihood) algorithm that uses a two-dimensional relaxation iterative search for estimating the range and velocity of multiple targets to get angle estimations suffers from slow computational speeds. In order to solve this issue, a new multi-target parameter estimator based on a space-time cascaded monopulse algorithm (M-STCMP) is proposed, which introduces the monopulse technique to the pulse domain for velocity measurement with temporal monopulse, leading to a one-dimensional search for range and a significant reduction in the computational burden of the two-dimensional iterative search in ACM-ML. Since the M-STCMP cannot simultaneously match multiple targets with varying velocities across the main beam with temporal monopulse, the algorithm estimates the velocity in each Doppler cell with the Doppler information of received signals. The estimation results produced in the main beams are iterated for each target to suppress energy leakage between targets and improve estimation accuracy. The effectiveness of the proposed algorithm is calculated by Monte Carlo simulation.
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