深圳大学学报理工版

针对天波超视距雷达(over-the-horizon radar, OTHR)多目标跟踪所面临的多路径和低检测概率问题,结合混合高斯概率假设密度(Gaussian mixture probability hypothesis density, GMPHD)滤波器免数据关联以及计算耗费低的优点,提出多路径不敏卡尔曼混合高斯概率假设密度(multipath unscented Kalman-Gaussian mixture probability hypothesis density, MPUK-GMPHD)融合框架.该框架将多路径效应等效为多传感器,构建面向OTHR的多传感器意义下的概率假设密度(probability hypothesis density, PHD)融合算法. 通过多路径信息的有效融合避免多路径独立量测更新带来PHD目标数过估问题,并采用不敏卡尔曼滤波处理量测模型非线性问题.仿真结果表明,在OTHR多目标跟踪的复杂环境下,MPUK-GMPHD融合算法能够较准确地估计目标状态和目标数,缓解了直接利用GMPHD滤波器处理带来的目标数过估和较大计算量的问题.

Sky wave over-the-horizon radar(OTHR)usually suffers from multipath propagation effects and low detection probabilities when tracking multiple targets. In this paper we present a multipath unscented Kalman-Gaussian mixture probability hypothesis density(MPUK-GMPHD)fusion framework to overcome these defects. The GMPHD filter is capable of avoiding data associations while maintaining low computational complexity. A probability hypothesis density fusion algorithm is proposed for OTHR, wherein multipath propagation effects are analyzed using a multi-sensor model. Particularly, the target number over-estimation problem is effectively avoided by fusing the multipath information, and an unscented Kalman filter is utilized to solve the nonlinear problem in measurement model. Simulation results show that the proposed MPUK-GMPHD framework estimates target state and number more accurately than conventional methods in complex environments, e.g. OTHR multi-target tracking. It overcomes the target number over-estimation and high computational complexity problems in existing GMPHD filter based algorithms.

引言
1 OTHR多目标跟踪问题描述及建模
2 多路径不敏卡尔曼混合高斯概率假
3 仿真验证
4 结语

图1 OTHR多路径示意图<br/>Fig.1 The sketch map of OTHR multipathx

图1 OTHR多路径示意图
Fig.1 The sketch map of OTHR multipathx

图2 单目标航迹图<br/>Fig.2 The single-target track

图2 单目标航迹图
Fig.2 The single-target track

图3 50次仿真平均OSPA距离图<br/>Fig.3 The mean OSPA distance of 10 simulations

图3 50次仿真平均OSPA距离图
Fig.3 The mean OSPA distance of 10 simulations

图4 三目标多路径量测信息<br/>Fig.4 The multipath measure of three targets

图4 三目标多路径量测信息
Fig.4 The multipath measure of three targets

图5 多目标航迹图<br/>Fig.5 The multi-target track

图5 多目标航迹图
Fig.5 The multi-target track

图6 MPUK-GMPHD多目标跟踪的OSPA距离图<br/>Fig.6 The OSPA distance f MPUK-GMPHD multi-target tracking

图6 MPUK-GMPHD多目标跟踪的OSPA距离图
Fig.6 The OSPA distance f MPUK-GMPHD multi-target tracking

图7 目标数估计图<br/>Fig.7 The estimated figure of the number of target

图7 目标数估计图
Fig.7 The estimated figure of the number of target

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备注

引言

1 OTHR多目标跟踪问题描述及建模

2 多路径不敏卡尔曼混合高斯概率假

3 仿真验证

4 结语

期刊信息

备注

引言

1 OTHR多目标跟踪问题描述及建模

2 多路径不敏卡尔曼混合高斯概率假

3 仿真验证

4 结 语

期刊信息

4 结语