非一致噪声下的多阵列直接定位算法

黄志英; 吴江; 唐涛; 王云龙

doi:10.7652/xjtuxb201510022

您当前的位置：

首页 >

文章列表页 >

非一致噪声下的多阵列直接定位算法

更新时间：2025-07-09

- 非一致噪声下的多阵列直接定位算法
- A Direct Position Determination Algorithm Based on Multi Arrays in the Presence of Unknown Nonuniform Noise
- 西安交通大学学报 2015年49卷第10期页码：136-142
- 作者机构：
  
  解放军信息工程大学信息系统工程学院,郑州,450001
- 作者简介：
- 基金信息：
  
  : 2015-01-09。作者简介: 黄志英(1987—),男,硕士生;吴江(通信作者),男,副教授,硕士生导师。基金项目: 国家自然科学基金资助项目(61201381)
- DOI：10.7652/xjtuxb201510022
  中图分类号： TN911.7
- 网络首发：2015-10-10，
  
  纸质出版：2015
- 稿件说明：
移动端阅览
黄志英, 吴江, 唐涛, 等. 非一致噪声下的多阵列直接定位算法[J]. 西安交通大学学报, 2015,49(10):136-142.

A Direct Position Determination Algorithm Based on Multi Arrays in the Presence of Unknown Nonuniform Noise[J]. 2015, 49(10): 136-142.
黄志英, 吴江, 唐涛, 等. 非一致噪声下的多阵列直接定位算法[J]. 西安交通大学学报, 2015,49(10):136-142. DOI： 10.7652/xjtuxb201510022.

A Direct Position Determination Algorithm Based on Multi Arrays in the Presence of Unknown Nonuniform Noise[J]. 2015, 49(10): 136-142. DOI： 10.7652/xjtuxb201510022.

摘要

针对实际无源定位系统中多个阵列分散分布以及单个阵列各阵元之间差异造成的噪声功率分布不均匀导致直接定位(DPD)算法精度下降的问题

提出了一种非一致高斯白噪声场中的多阵列最大似然DPD(UN-ML-DPD)算法

并推导出该条件下的克拉美罗界。首先计算各阵列输出协方差矩阵; 再将计算结果传到数据处理中心; 然后由数据中心通过迭代的方式同时对目标位置与非一致噪声功率进行最大似然联合估计

以收敛后得到的结果作为目标位置精确估计值

从而减弱了非一致噪声对DPD算法的影响; 最后在多目标条件下用交替投影法降低算法复杂度。较之传统算法

UN-ML-DPD算法能够提高多阵列在低信噪比下的定位精度。仿真结果表明:UN-ML-DPD算法在-15 dB的低信噪比下估计误差小于15 km

与DPD算法相比定位精度提高15%以上; 能较为准确地估计各阵列噪声协方差矩阵

在标准噪声功率小于30 W时估计误差小于3.5 W; 在高信噪比下定位精度能够逼近克拉美罗下界。

Abstract

A multi-array based maximum likelihood direct position determination(DPD)algorithm in the presence of unknown nonuniform noise(UN-ML-DPD)is proposed and an expression of Cramér-Rao lower bound(CRLB)is derived to solve the problem that the position accuracy of the DPD algorithm decreases due to dispersed multi-array distribution and nonuniform noise power distribution caused by difference among array elements in passive localization systems. The covariance matrixes of the array data are calculated and the results are transmitted to the process center. Then

the power of the nonuniform noise and the position of the targets are co-estimated simultaneously using the maximum likelihood method with iteration

and the converged result is taken as the target position estimation

so that the effect of the nonuniform noise is reduced. The alternative projection method is utilized to lower the algorithm complexity when multi targets exist. Compared with the traditional method

the UN-ML-DPD algorithm can improve the position accuracy under low signal-to-noise ratio(SNR). Simulation results show that the estimation error is lower than 15 km for SNR is -15 dB

and the accuracy of the position estimation is increased by 15% compared with the DPD method. The noise covariance matrix is well estimated

and the estimation error is less than 3.5 W when the standard power of the noise is lower than 30 W. Moreover

the position accuracy approaches the CRLB when the SNR are high.

关键词

Keywords

references

王鼎, 吴瑛, 田建春. 基于总体最小二乘算法的多站无源定位 [J]. 信号处理, 2007, 23(4): 611-614.

WANG Ding, WU Ying, TIAN Jianchun. Multi-station passive location based on TLS algorithm [J]. Signal Processing, 2007, 23(4): 611-614.

王鼎, 张莉, 吴瑛. 基于角度信息的结构总体最小二乘无源定位算法 [J]. 中国科学: F辑信息科学, 2009, 39(6): 663-672.

WANG Ding, ZHANG Li, WU Ying. The structured total least squares algorithm research for passive location based on angle information [J]. Science in China: Series F Information Science, 2009, 39(6): 663-672.

王云龙, 吴瑛. 联合时延与多普勒频率的直接定位改进算法 [J]. 西安交通大学学报, 2015, 49(4): 123-129.

WANG Yunlong, WU Ying. An improved direct position determination algorithm with combined time delay and Doppler [J]. Jounal of Xi'an Jiaotong University, 2015, 49(4): 123-129.

WEISS A J. Direct position determination of narrowband radio frequency transmitters [J]. IEEE Signal Processing Letters, 2004, 11(5): 513-516.

AMAR A, WEISS A J. Advances in direct position determination [C]∥ Proceedings of 2004 Sensor Array and Multichannel Signal Processing Workshop. Los Alamitos, CA, USA: IEEE Computer Society, 2004: 584-588.

WEISS A J, AMAR A. Direct position determination of multiple radio signals [J]. EURASIP Journal on Applied Signal Processing, 2005(1): 37-49.

AMAR A, WEISS A J. Direct position determination in the presence of model errors: known waveforms [J]. Digital Signal Processing, 2006, 16: 52-83.

DEMISSIE B, OISPUU M, RUTHOTTO E. Localization of multiple sources with a moving array using subspace data fusion [C]∥ 11th International Conference on Information Fusion. Piscataway, NJ, USA: IEEE, 2008: 1-7.

OISPUU M, NICKEL U. Direct detection and position determination of multiple sources with intermittent emission [J]. Signal Processing, 2010, 90: 3056-3064.

张敏, 郭福成, 周一宇. 基于单个长基线干涉仪的运动单站直接定位 [J]. 航空学报, 2013, 34(2): 378-386.

ZHANG Min, GUO Fucheng, ZHOU Yiyu. A single moving observer direct position determination method using a long baseline interferometer [J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(2): 378-386.

孙俊, 方伟, 吴小俊, 等. 量子行为粒子群优化: 原理及其应用 [M]. 北京: 清华大学出版社, 2011.

PESAVENTO M, GERSHMAN A B. Maximum-likelihood direction-of-arrival estimation in the presence of unknown nonuniform noise [J]. IEEE Transactions on Signal Processing, 2001, 49(7): 1310-1324.

王永良, 陈辉, 彭应宁. 空间谱估计理论与算法 [M]. 北京: 清华大学出版社, 2004.

王云龙,吴瑛.联合时延与多普勒频率的直接定位改进算法.2015,49(4):123-129.[doi:10.7652/xjtuxb201504020]

张东伟,郭英,齐子森,等.采用空间极化时频分布的跳频信号多参数联合估计算法.2015,49(8):17-23.[doi:10.7652/xjtuxb201508004]

巴斌,郑娜娥,朱世磊,等.利用蒙特卡罗的最大似然时延估计算法.2015,49(8):24-30.[doi:10.7652/xjtuxb201508005]

吴一全,孟天亮,吴诗婳.人工蜂群优化的非下采样Shearlet域引导滤波图像增强.2015,49(6):39-45.[doi:10.7652/xjtuxb201506007]

熊涛,江桦,崔鹏辉,等.应用基扩展模型的混合信号单通道盲分离算法.2015,49(6):60-66.[doi:10.7652/xjtuxb201506 010]

尚佳栋,王祖林,周丽娜,等.采用随机共振增强的混合扩频信号跳频参数估计.2014,48(10):42-48.[doi:10.7652/xjtuxb201410007]

吴杰,冯祖仁,刘恒,等.水下目标多元声传感阵列网络定位方法.2015,49(4):40-45.[doi:10.7652/xjtuxb201504007]

李彬,王文杰,殷勤业,等.无线传感器网络节点协作的节能路由传输.2012,46(6):1-6.[doi:10.7652/xjtuxb201206001]

朱磊,水鹏朗,章为川,等.利用区域划分的合成孔径雷达图像相干斑抑制算法.2012,46(10):83-88.[doi:10.7652/xjtuxb201210015]

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

正交频分复用分组传输系统中载波频偏和信道的联合估计

非线性最优机器人手眼标定

噪声不一致背景下脉冲串辐射源直接定位算法

电动车辆间接热系统快速除湿响应迟滞机理及优化控制策略

结构-语义-残差协同的图像压缩框架：面向隐私保护与高保真重建