Abstract
In continuous wave (CW) radar and high pulse repetition frequency pulse-Doppler (HPRF-PD) radar, the interference plus noise sample snapshots are hard to be obtained. The desired signal in the received snapshots makes the LCMV-based adaptive monopulse algorithm sensitive to pattern look direction error. A linearly constrained subarray robust adaptive monopulse algorithm based on main lobe maintenance constraint and subspace tracking is developed in this paper. The constraint of main lobe maintenance is obtained by signal subspace projection. The bi-iterative least-square (Bi-LS) subspace tracking is used to update the signal subspace, and a power-associated method is developed to determine the dimension of the projection subspace automatically. The proposed robust adaptive monopulse algorithm can achieve high-angle estimation accuracy and good robustness to look direction error while expending only one additional degree of freedom compared to conventional LCMV-based method.
Highlights
The monopulse technique is utilized to perform high precision angle estimation for tracking radars
3.1 Robust linearly constrained minimum variance (LCMV) beamformer with main lobe maintenance constraint (RMM-LCMV) In order to relieve the pattern distortion caused by look direction error, an RMM-LCMV beamformer is developed for forming the sum and difference beams
The results demonstrate that the proposed method can obtain higher performance than robust adaptive beamforming (RAB) with multidirectional constraints and RAB with derivative constraints, and only costs one additional DOF compared to conventional LCMV algorithm
Summary
The monopulse technique is utilized to perform high precision angle estimation for tracking radars. In the adaptive monopulse angle tracking, the signal of interest (SOI) may be present in any direction inside the 3dB beam scope, which may cause the distortion of the sum and difference patterns formed by linearly constrained minimum variance (LCMV) algorithm [10]. For conventional LCMV-based monopulse algorithm [6], the response in the pattern look direction is constrained, and the output power of the beamformer is minimized. The pattern look direction in the current monopulse processing period is fixed and provided by the angle tracking loop filter. The main lobes of the sum and difference beams formed by the conventional LCMV algorithm will be distorted, and angle estimation performance will be degraded. A robust LCMV beamformer with constraints on main lobe maintenance and monopulse ratio curve is developed to obtain the sum and difference beam outputs. The angle of SOI is estimated using sum and difference beam outputs
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