基于动态规划的机动目标加权自适应相参积累方法

陈帅霖; 罗丰; 张林让; 胡冲; 陈世超

doi:10.12000/JR17002

基于动态规划的机动目标加权自适应相参积累方法

doi: 10.12000/JR17002

西安电子科技大学雷达信号处理国家重点实验室西安 710071

基金项目: 国家部委基金(4010101030101)，国家重大科学仪器设备开发专项资金(2013YQ20060705)

详细信息

作者简介:
陈帅霖(1986–)，男，西安电子科技大学雷达信号处理国家重点实验室博士生，研究方向为杂波背景下的目标检测与跟踪。E-mail: chenshuailin@live.cn

罗　丰(1971–)，男，西安电子科技大学雷达信号处理国家重点实验室博士生导师，教授，研究方向为雷达系统设计、雷达信号与信息处理、高速实时信号处理。E-mail: luofeng@xidian.edu.cn

张林让(1966–)，男，西安电子科技大学雷达信号处理国家重点实验室博士生导师，教授，研究方向为雷达系统建模仿真与评估、阵列信号处理、自适应信号处理。E-mail: lrzhang@xidian.edu.cn

胡冲：胡冲(1987–)，男，西安电子科技大学雷达信号处理国家重点实验室博士生，研究方向为海杂波特性分析与建模。E-mail: hake_hc@163.com

陈世超(1992–)，女，西安电子科技大学雷达信号处理国家重点实验室博士生，研究方向为基于深度学习的雷达目标检测。E-mail: scchen@stu.xidian.edu.cn

通讯作者:
罗丰 luofeng@xidian.edu.cn

中图分类号: TN957.51
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出版历程
- 收稿日期: 2017-01-03
- 修回日期: 2017-03-15
- 网络出版日期: 2017-06-28

Weighted Adaptive Step Coherent Integration Method for Maneuvering Target Based on Dynamic Programming

National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds: The National Ministries Foundation (4010101030101), The National Key Scientific Instrument and Equipment Development Project Funds (2013YQ20060705)

摘要

摘要: 针对机动目标径向速度变化和距离徙动与多普勒扩展的耦合关系，该文提出一种基于动态规划的加权自适应相参积累(DPWACI)方法。该方法能够沿着目标运动轨迹进行高效能量积累。首先，加权的动态规划过程能够精确搜索目标各时刻的位置与速度；其次，改进的相参积累能够对整个过程中的相位扩展进行多普勒校正；最后，自适应步长能够在不同速度搜索通道采用相应的相参积累时间。该算法无需估计具体运动参数，适用于任意机动方式。仿真结果和性能对比展示了该算法的估计精确性以及相较于传统算法的优越性。
- 加权矩阵 /
- 自适应步长 /
- 动态规划 /
- 相参积累 /
- 机动目标
Abstract: In allusion to the coupling relationship among radial velocity variation, range migration, and Doppler spread of a maneuvering target, a Dynamic Programing (DP)-based Weighted Adaptive Coherent Integration (DPWACI) detection method is proposed. The target energy could be efficiently integrated along its trajectory by the proposed method. The main idea of DPWACI is the joint execution of the three operations: the weighted DP procedure that could accurately search the current position and velocity of the target; the improved coherent integration that could calibrate the Doppler shift during the entire process with a large phase spread; and the adaptive step that could make the integration time suitable for each velocity searching bin. The proposed method is applicable to a target with an arbitrary motion without estimating its specific movement parameters. Simulation results and performance comparisons show the exactitude and superiority of the proposed method.
- Weighting matrix /
- Adaptive step /
- Dynamic Programming (DP) /
- Coherent integration /
- Maneuvering target

HTML全文

图 1 本文算法流程图

Figure 1. Flow chart of this paper algorithm

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图 2 权系数曲线

Figure 2. Curve of weight coefficient

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图 3 DPWACI处理结果

Figure 3. Result of DPWACI

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图 4 MTD处理结果

Figure 4. Result of MTD

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图 5 RFT处理结果

Figure 5. Result of RFT

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图 6 检测性能对比曲线

Figure 6. Curves of comparison of detection performances

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图 7 速度估计均方根误差

Figure 7. Root mean square error of estimated velocity

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