To achieve full coherence, it is indispensable for distributed coherent aperture radar (DCAR) to estimate coherence parameters (CPs) using orthogonal waveforms in MIMO mode. However, incomplete orthogonality between waveforms and initial time and phase synchronization errors between the subapertures introduce estimation errors, which degrade full coherence performance. To tackle these issues, we propose an orthogonal waveform design framework based on ambiguity function (AF) shaping to improve CPs' estimation accuracy. We combine the alternating direction method of multipliers (ADMM) and the majorization-minimization (MM) algorithm to transform the nonconvex quartic optimization problem into a quadratic optimization problem. Numerical simulation results show that the optimized waveforms significantly enhance the estimation accuracy of CPs.
Transmit Waveform Design Based on Ambiguity Function Shaping for Distributed Coherent Aperture Radar in MIMO Mode
Greco M.Membro del Collaboration Group
;Gini F.Membro del Collaboration Group
;
2024-01-01
Abstract
To achieve full coherence, it is indispensable for distributed coherent aperture radar (DCAR) to estimate coherence parameters (CPs) using orthogonal waveforms in MIMO mode. However, incomplete orthogonality between waveforms and initial time and phase synchronization errors between the subapertures introduce estimation errors, which degrade full coherence performance. To tackle these issues, we propose an orthogonal waveform design framework based on ambiguity function (AF) shaping to improve CPs' estimation accuracy. We combine the alternating direction method of multipliers (ADMM) and the majorization-minimization (MM) algorithm to transform the nonconvex quartic optimization problem into a quadratic optimization problem. Numerical simulation results show that the optimized waveforms significantly enhance the estimation accuracy of CPs.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.