Underwater target localization method by removing the unreliable measurements based on SVDD
PANG Feifei1,WEN Xiangxi2,WANG Xiaohua1
1. School of Electronics and Information, Xi’an Polytechnic University, Xi’an 710048, China；
2. Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, China
摘要复杂多变的水声环境使一些传感器节点估计方位角时出现异常值，降低了水下目标的定位精度。针对这一问题，本文利用高斯混合模型对方位角的观测模型进行建模，基于支持向量数据描述（support vector data description，SVDD）方法提出去除方位异常值的水下目标定位方法。该方法将目标定位与异常值识别有机结合，利用正常观测和异常观测下目标初始估计位置分布特征不同的特点，使用SVDD方法对这些初始估计位置分类从而识别出异常值，最后将异常值剔除、利用剩余方位信息完成对目标的最终定位。计算机仿真结果证明了所提方法的有效性。
Abstract：The angle-of-arrival (AOA) measurements taken by the sensors could be unreliable in the complex and changeable underwater environment, leading to a degradation of the target localization performance. To improve the localization performance, this paper uses a mixture model of Gaussian distribution and uniform distribution to model the AOA measurements, and proposes a target localization approach by removing the unreliable measurements based on the support vector data description (SVDD) method. Based on the different distribution characteristics of the target location initialization under the cases of normal and unreliable measurement, the proposed method integrates the target localization into the detection of the unreliable measurements, and employs SVDD algorithm to classify the target location initialization. As a result, the unreliable AOA measurements can be figured out and removed. Finally, the target location is obtained with the rest measurements. The simulation results demonstrate the effectiveness of the proposed localization method.
庞菲菲1，温祥西2，王晓华1. 基于SVDD去除异常值的水下目标定位方法[J]. 振动与冲击, 2021, 40(22): 182-187.
PANG Feifei1,WEN Xiangxi2,WANG Xiaohua1. Underwater target localization method by removing the unreliable measurements based on SVDD. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(22): 182-187.
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