| 方位和径向速度联合的浅海目标运动分析方法 |
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| 引用本文： | 徐鹏, 郭良浩, 闫超, 周明阳. 方位和径向速度联合的浅海目标运动分析方法[J]. 声学学报, 2018, 53(3): 323-333. DOI: 10.15949/j.cnki.0371-0025.2018.03.007 |
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| 作者姓名： | 徐鹏 郭良浩 闫超 周明阳 |
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| 作者单位： | 1. 中国科学院声学研究所 声场声信息国家重点实验室 北京 100190; |
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| 基金项目： | 国家自然科学基金项目(61571436)资助 |
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| 摘 要： | 提出了一种利用目标方位和径向速度联合的浅海目标运动分析方法。该方法克服了传统纯方位目标运动分析方法要求观测站机动的局限性。将浅海传播条件下径向速度的宽带和窄带估计结果与目标方位相结合,利用卡尔曼滤波原理得到了一种目标跟踪定位方法。仿真结果表明,在观测站非机动和低信噪比情况下,该方法利用单个观测站即能够对宽带或窄带的运动目标进行准确地跟踪定位。利用1996年5月的实验数据对算法性能进行了验证,估计结果与真实目标距离符合较好,距离跟踪误差在10%以内。
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| 关 键 词： | 目标运动分析 浅海 纯方位 径向速度 卡尔曼滤波 |
| 收稿时间： | 2017-08-18 |
| 修稿时间： | 2018-01-17 |
Target motion analysis method using bearing and radial velocity in shallow water |
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| XU Peng, GUO Lianghao, YAN Chao, ZHOU Mingyang. Target motion analysis method using bearing and radial velocity in shallow water[J]. ACTA ACUSTICA, 2018, 53(3): 323-333. DOI: 10.15949/j.cnki.0371-0025.2018.03.007 |
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| Authors: | XU Peng GUO Lianghao YAN Chao ZHOU Mingyang |
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| Affiliation: | 1. State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences Beijing 100190;2. University of Chinese Academy of Sciences Beijing 100049 |
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| Abstract: | A target motion analysis method using bearing and radial velocity in shallow water is proposed. This method overcomes the limitation that the observer must be maneuverable. First, two different radial velocity estimation methods for broadband and narrowband target are studied. Then, based on the measurement parameters of bearing and radial velocity fusion, a extended Kalman filter is obtained in Cartesian coordinates. Simulation results show that the proposed method can fastly and accurately track a broadband or narrowband moving target by a single observer in low signal-to-noise ratio environment when the observer is nonmaneuverable. The effectiveness of the method is verified by using the experimental data. The estimated result is close to the real value and the mean relative error of target range tracking is within 10%. |
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| Keywords: | target motion analysis shallow water bearings-only radial velocity Kalman filter |
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