Yibin Liu;Shengbin Luo Wang;Guoqing Wu;Ping Wang;Yongzhen Li
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引用次数: 0
Abstract
Four-channel monopulse (FCM) technique is integral to contemporary radar systems for pinpointing and tracking multiple targets. However, the practical utility of FCM is significantly hindered by the issue of estimation failure, which arises from the specific relative phases and positions of the targets. In this paper, we introduce a polarimetric four-channel monopulse (PFCM) approach designed to deliver efficient, robust, and unambiguous resolution of two targets. Generally, PFCM adaptively modulates the null-polarization for each target. We begin by dissecting the limitations of the traditional method, utilizing the closed-form solution of FCM. Subsequently, we devise a novel closed-form solution that harnesses polarimetric adaptive nulling (PAN) technology to estimate the angles of the two targets under two distinct scenarios: the ideal condition and angular ambiguity. Under ideal conditions, estimation is conducted directly using the received signals. Incorporating polarization information mitigates the estimation results’ sensitivity to relative phase. To counteract the challenges of PAN failure in angular ambiguity situations, the proposed PFCM adeptly resolves the two targets by reconstructing the four-channel signal, indicating its applicability across various relative target positions. Furthermore, we present a comprehensive performance analysis focusing on three critical aspects. As a result, two closely spaced targets can be resolved robustly and unambiguously with minimal complexity. Numerical simulations and experimental results are substantiated to validate the effectiveness of the proposed method.
期刊介绍:
The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.