收发基线附近多基地雷达多普勒测量融合的可观测性分析
Observability Analysis for Fusion of Doppler Measurements in Multistatic Radar Near the Tx-Rx Baseline
浏览论文内容
中文总结 AI 辅助
本文针对收发基线附近多基地雷达的目标轨迹估计难题，分析该区域的可观测性，提出仅用多普勒测量的融合方法，经仿真验证有效。
中文摘要 AI 辅助
本文研究目标位于收发（Tx-Rx）基线模糊区时的多基地测量融合问题，尤其关注包含两个间距很近的固定收发对的配置。与稀疏间距的多基地系统相比，此类配置提供重叠的可探测区域并扩展有效探测范围。但在该区域内，距离和方位测量的精度会迅速下降，多普勒测量往往仍是唯一可靠的信息源，导致目标轨迹估计极具挑战性，可观测性处于边缘状态甚至完全丧失。为解决该问题，本文在不同条件下分析目标轨迹的可观测性，使系统设计者能提前评估系统性能。随后开发仅基于多普勒的测量融合方法，采用多初始点最大似然（ML）非线性估计器进行初始状态估计，再通过扩展卡尔曼滤波（EKF）进行动态状态更新。仿真结果表明与可观测性分析一致。
英文摘要
This paper studies multistatic measurement fusion when a target lies within the Tx--Rx (Transmitter-Receiver) baseline ambiguity zone, with particular emphasis on configurations involving two closely spaced stationary Tx--Rx pairs. Such configurations provide overlapping detectable regions and extend the effective detection range compared with sparsely spaced multistatic systems. However, in this region, the accuracy of range and bearing measurements degrades rapidly, and Doppler measurements often remain the only reliable information source. As a result, target trajectory estimation becomes highly challenging, with observability being marginal or even completely lost. To address this problem, the observability of target trajectories is analyzed under various conditions, enabling system designers to assess system performance in advance. A Doppler-only measurement fusion approach is then developed, employing a multiple-initial-point Maximum Likelihood (ML) nonlinear estimator for initial state estimation, followed by dynamic state updates using an Extended Kalman Filter (EKF). Simulation results are presented and shown to be consistent with the observability analysis.
