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Optimal array structure for time difference direction finding based on improved particle swarm optimization
Received date: 2021-10-11
Revised date: 2021-11-18
Accepted date: 2022-04-11
Online published: 2022-04-24
Supported by
Key Research Program of the Chinese Academy Science(KFZD-SW-437)
To reduce the impact of the array structure on the accuracy of the direction finding algorithm and improve the accuracy of target direction finding in specific scenarios, a Particle Swarm Optimization algorithm with Competitive and Differential Evolution (PSO-CDE) is proposed to optimize the time difference direction finding array. First, according to the principle of time difference direction finding, the sensor array is designed with position and baseline constraints. The fitness evaluation function is constructed with the mean square error. Second, the PSO-CDE algorithm is proposed to improve particle swarm optimization performance and robustness and optimize the array structure. Finally, the optimized array structure under different conditions is obtained by simulating the target range environment. The results show that the optimized array has higher accuracy in target direction finding than the regular array. The influence of the array element baseline, the number of the elements and the time delay error in the optimal array on the accuracy of direction finding is also analyzed, which provides a reference for the selection of array structure optimization strategy in the actual scene.
Ping JIANG , Bingnan QU , Huaze DING , Runze MA , Wei HE . Optimal array structure for time difference direction finding based on improved particle swarm optimization[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(2) : 326502 -326502 . DOI: 10.7527/S1000-6893.2022.26502
1 | SHAN L H, FANG W D, QIU Y Z, et al. Smart mobile gateway: Technical challenges for converged wireless sensor networks and mobile cellular networks[J]. International Journal of Future Generation Communication and Networking, 2016, 9(9): 87-98. |
2 | 李超. 基于粒子群算法的测向定位布站优化[J]. 指挥信息系统与技术, 2021, 12(1): 76-79. |
LI C. Direction finding location placement optimization based on particle swarm optimization[J]. Command Information System and Technology, 2021, 12(1): 76-79 (in Chinese). | |
3 | 谢鑫. 测向交叉定位最优布站方案分析[J]. 电子科技, 2014, 27(8): 85-89. |
XIE X. Analysis of optimal scheme of direction finding cross station distribution[J]. Electronic Science and Technology, 2014, 27(8): 85-89 (in Chinese). | |
4 | 屈秉男, 蒋平, 赵鲁阳, 等. 基于短基线传感器阵列的炮弹被动测向算法[J]. 航空学报, 2022, 43(3): 400-414. |
QU B N, JIANG P, ZHAO L Y, et al. Passive direction finding algorithm of projectile based on short baseline sensor array[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43(3): 400-414 (in Chinese). | |
5 | 王玉龙, 刘艳红, 卢小汐, 等. 大范围散布弹丸落点测量最优布站方法[J]. 舰船电子工程, 2021, 41(4): 156-160. |
WANG Y L, LIU Y H, LU X X, et al. Research on the optimal station method of the forward intersection measurement of the projectile drop point[J]. Ship Electronic Engineering, 2021, 41(4): 156-160 (in Chinese). | |
6 | 霍鹏举, 黄勇, 刘亮. 弹着点定位系统中初至信号拾取方法[J]. 兵器装备工程学报, 2017, 38(8): 112-116, 130. |
HUO P J, HUANG Y, LIU L. On the methods of first arrival identification in positing system of the impact point[J]. Journal of Ordnance Equipment Engineering, 2017, 38(8): 112-116, 130 (in Chinese). | |
7 | CHAN Y T, HO K C. A simple and efficient estimator for hyperbolic location[J]. IEEE Transactions on Signal Processing, 1994, 42(8): 1905-1915. |
8 | WANG Y, HO K C. TDOA positioning irrespective of source range[J]. IEEE Transactions on Signal Processing, 2017, 65(6): 1447-1460. |
9 | 贾思宇, 路茗, 丁华泽, 等. 一种改进的信号子空间聚焦宽带DOA估计算法[J]. 计算机工程, 2022, 48(1): 175-181. |
JIA S Y, LU M, DING H Z, et al. A modified wideband DOA estimation algorithm for focusing signal subspace[J]. Computer Engineering, 2022, 48(1): 175-181 (in Chinese). | |
10 | 侯东升, 崔逊学. 基于莱温伯格-马夸特的TDOA测向算法研究[J]. 计算机工程, 2018, 44(11): 109-114. |
HOU D S, CUI X X. Research of TDOA direction finding algorithm based on levenberg-marquardt[J]. Computer Engineering, 2018, 44(11): 109-114 (in Chinese). | |
11 | 王程民, 平殿发, 张涵. 几种典型编队的多机无源定位布站分析[J]. 舰船电子工程, 2019, 39(7): 37-41. |
WANG C M, PING D F, ZHANG H. Analysis of multi-aircraft passive location stations of several aircraft formations[J]. Ship Electronic Engineering, 2019, 39(7): 37-41 (in Chinese). | |
12 | 金博楠, 徐晓苏, 张涛, 等. 基于TDOA定位的阵列布放结构研究[J]. 导航定位与授时, 2017, 4(6): 29-36. |
JIN B N, XU X S, ZHANG T, et al. Study of array structure for sensor placement in TDOA-based localization[J]. Navigation Positioning and Timing, 2017, 4(6): 29-36 (in Chinese). | |
13 | 李世豪, 王建. 非规则布站对时差系统定位精度的影响分析[J]. 电子科技, 2020, 33(10): 57-63. |
LI S H, WANG J. Analysis of influences of irregular station arrangement on location accuracy of TDOA system[J]. Electronic Science and Technology, 2020, 33(10): 57-63 (in Chinese). | |
14 | LIU H T, KIRUBARAJAN T, XIAO Q. Arbitrary microphone array optimization method based on TDOA for specific localization scenarios[J]. Sensors (Basel, Switzerland), 2019, 19(19): 4326. |
15 | 曹孟华, 李龙, 谢红卫. 改进遗传算法在传声器阵列优化中的应用[J]. 国防科技大学学报, 2019, 41(6): 126-134. |
CAO M H, LI L, XIE H W. Application of improved genetic algorithm in microphone array optimization[J]. Journal of National University of Defense Technology, 2019, 41(6): 126-134 (in Chinese). | |
16 | STORN R, PRICE K. Differential evolution–A simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11: 341-359. |
17 | 夏伟, 罗明, 赵美霞. 无源时差定位系统最优布站方法研究[J]. 雷达科学与技术, 2020, 18(1): 34-38. |
XIA W, LUO M, ZHAO M X. Study on optimal station distribution and performance of passive time difference localization system[J]. Radar Science and Technology, 2020, 18(1): 34-38 (in Chinese). | |
18 | 赵忠凯, 刘楯, 黄湘松. 无人机编队时差定位时的空间布局分析[J]. 应用科技, 2021, 48(2): 12-18, 41. |
ZHAO Z K, LIU D, HUANG X S. Analysis of spatial layout for unmanned aerial vehicle formation time difference of arrival location[J]. Applied Science and Technology, 2021, 48(2): 12-18, 41 (in Chinese). | |
19 | BERDUGO B, DORON M A, ROSENHOUSE J, et al. On direction finding of an emitting source from time delays[J]. The Journal of the Acoustical Society of America, 1999, 105(6): 3355-3363. |
20 | CUI X X, YU K G, LU S S. Approximate closed-form TDOA-based estimator for acoustic direction finding via constrained optimization[J]. IEEE Sensors Journal, 2018, 18(8): 3360-3371. |
21 | 刘砚菊, 胡杨, 于洋, 等. 基于改进粒子群算法的复杂地况下雷达布站优化[J]. 火力与指挥控制, 2014, 39(9): 164-168. |
LIU Y J, HU Y, YU Y, et al. Study of radar deployment under complex terrain environment based on improved PSO[J]. Fire Control & Command Control, 2014, 39(9): 164-168 (in Chinese). | |
22 | 张春韵, 邹德旋, 沈鑫. 改进的粒子群算法在电力经济调度中的应用[J]. 制造业自动化, 2021, 43(1): 53-57, 64. |
ZHANG C Y, ZOU D X, SHEN X. Application of improved particle swarm optimizational gorithm in power economic dispatching[J]. Manufacturing Automation, 2021, 43(1): 53-57, 64 (in Chinese). | |
23 | 吴虎胜, 张凤鸣, 吴庐山. 一种新的群体智能算法: 狼群算法[J]. 系统工程与电子技术, 2013, 35(11): 2430-2438. |
WU H S, ZHANG F M, WU L S. New swarm intelligence algorithm—wolf pack algorithm[J]. Systems Engineering and Electronics, 2013, 35(11): 2430-2438 (in Chinese). | |
24 | 丁超, 戴卫国, 王森, 等. 基于几何精度稀释的矢量潜标最优布站[J/OL]. 系统工程与电子技术, 2021, 43(11): 3107-3117. |
DING C, DAI W G, WANG S, et al. Optimal disposition of vector submerged buoy array based on geometrical dilution of precision[J/OL]. Systems Engineering and Electronics, 2021, 43(11): 3107-3117 (in Chinese). |
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