为解决组网雷达对目标跟踪中的量测非线性问题,提出基于最佳线性无偏估计器(BLUE)准则的融合滤波方法。建立以融合中心为原点的组网雷达对目标定位的量测方程,推导出极坐标系与球坐标系下跟踪目标的BLUE滤波模型。理论分析表明,集中式BLUE滤波架构在估计单个雷达量测转换误差统计特性的同时,还估计出雷达间量测转换误差的统计特性。因此,跟踪精度和置信度较分布式BLUE滤波方法有显著提高,计算量较其他算法也有明显优势。不同场景下的仿真分析证明:该方法在不同状态噪声水平下的表现优异,是一种很有竞争力的跟踪算法。

To solve the nonlinear measurements problem of target tracking by netted radar, a centralized fusion filtering scheme based on boest linear unbiased estimation( BLUE) principle is proposed. Assuming the fusion center as coordinate origin, the measurement equation of target location by multiple radars is given, the BLUE filter models for target tracking by multiple radars with spherical and polar measurements are derived separately. Theoretic analysis shows centralized BLUE filter framework can estimate not only converted measurements' statistical characteristic of single radar, but also the statistical characteristic of converted measurements from multiple radars, so it outperforms distributed BLUE filter in both tracking precision and filter credibility. Computation complexity of centralized BLUE filter is relatively low as well. Simulations for different target profiles show that the proposed algorithm is superior to others in tracking scene with different state noise levels, which makes it a competitive filtering tracking method.

TN713

安徽省自然科学基金项目