多跳频信号频率跟踪与二维波达方向实时估计算法

张东伟; 郭英; 张坤峰; 齐子森; 韩立峰; 尚耀波

doi:10.11999/JEIT151170

多跳频信号频率跟踪与二维波达方向实时估计算法

doi: 10.11999/JEIT151170

2.
(空军工程大学装备发展与运用研究中心西安 710051) ②(空军工程大学信息与导航学院西安 710077)

基金项目:

国家自然科学基金(61401499)，陕西省电子信息系统综合集成重点实验室基金(201501A)，航空科学基金(20112096016)

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出版历程
- 收稿日期: 2015-10-23
- 修回日期: 2016-07-01
- 刊出日期: 2016-09-19

Online Estimation Algorithm of 2D-DOA and Frequency Tracking for Multiple Frequency-hopping Signals

2.
ZHANG Dongwei①② GUO Ying② ZHANG Kunfeng② QI Zisen② HAN Lifeng① SHANG Yaobo

Funds:

The National Natural Science Foundation of China (61401499), The Foundation of Electronic Information System Integration Laboratory in Shaanxi Province (201501A)，The Aviation Science Foundation of China (20112096016)

摘要

摘要: 为了实时提取跳频(FH)通信参数以及为通信对抗提供所需信息，该文提出一种多跳频信号频率跟踪和2维波达方向实时估计算法。首先建立跳频信号的L型阵列接收数据模型，并推导证明了自回归滑动平均(ARMA)模型对L型阵列数据的适用性，然后采用粒子滤波思想对阵列流型矩阵和频率进行实时估计。再基于频率估计值建立ARMA模型实时检测跳时刻，并结合流型矩阵估计值实现无需参数配对的2维波达方向(2D-DOA)准确估计。新方法通过设计合理的粒子生成以及权值更新方式，使流型矩阵与频率估计值能够迅速收敛至稳定状态。最后蒙特卡罗仿真结果验证了该算法的有效性。
- 信号处理 /
- 跳频 /
- 频率估计 /
- 波达方向 /
- 粒子滤波 /
- 自回归滑动平均模型
Abstract: In order to extract Frequency-Hopping (FH) communication parameters and provide the necessary information for the communication countermeasure, an online estimation algorithm of 2D-DOA and frequency tracking for multiple FH signals is proposed in this paper. Firstly, the data model of the L-array for FH signals is built and the applicability of Auto Regresive Moving Average (ARMA) model to L-array data is proved. Then, the particle filtering is introduced to conduct the online estimation of manifold matrix and the frequency, and the ARMA model is built based on the frequency estimates, depending on which, the online detection of hop timing is obtained. After that , the precise estimation of 2D-DOA can be gained via manifold matrix estimates and without parameter matching. With the rational method of particle generation and the weight updating, the new method makes the estimates of manifold matrix and the frequency reach to the stable value promptly. Finally the the Monte-Carlo simulation results show the effectiveness of the proposed algorithm.
- Signal processing /
- Frequency-Hopping (FH) /
- Frequency estimation /
- Direction Of Arrival (DOA) /
- Particle filtering /
- Auto Regresive Moving Average (ARMA) model

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参考文献(21)

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