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对于机载脉冲多普勒雷达,多普勒盲区是不可避免的。为解决多普勒盲区内机动目标跟踪问题,提出了基于扩展卡尔曼粒子滤波(IMMEPF)的雷达和ESM联合跟踪算法。该算法融合了交互式多模型(IMM)、粒子滤波(PF)和扩展卡尔曼滤波(EKF)的优势,采用多模型结构以匹配目标的运动模型。粒子滤波能处理非线性、非高斯问题,而采用EKF产生粒子,由于考虑了当前观测值,使得粒子的分布更接近后验概率密度分布,克服粒子的退化现象,从而提高估计精度。仿真结果表明,给出的算法能够显著提高对落入多普勒盲区内的目标点迹的跟踪精度。
For airborne pulsed Doppler radar, Doppler blind spots are inevitable. In order to solve the problem of maneuvering target tracking in the Doppler blind region, a joint radar and ESM tracking algorithm based on Extended Kalman Filter (IMMEPF) is proposed. The algorithm combines the advantages of IMM, PF and EKF, and uses a multi-model structure to match the target’s motion model. Particle filter can deal with non-linear and non-Gaussian problems. EKF is used to generate particles. Due to the current observed values, the particle distribution is closer to the posterior probability density distribution, which can overcome the degradation of particles and improve the estimation accuracy. The simulation results show that the proposed algorithm can significantly improve the tracking accuracy of the target spot that falls into the Doppler blind spot.