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A Self-Adaptive Modified Angle Filtering Algorithm Based on Passive Tracking Environment |
LIU Xiaoyang1, XU Weili2, CHEN Jiming1, XU Peiran1, ZHOU Xiangxiang1 |
1. Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109, China;
2. Shanghai Academy of Spaceflight Technology, Shanghai 201109, China |
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Abstract In view of poor filtering and noise reduction of target angle data in passive tracking, this paper proposes a self-adaptive modified angle filtering algorithm. It introduces the pseudo-acceleration and obtains the adaptive filter gain by accumulating the residual error of data over a certain period of time. This algorithm has an important engineering significance. For the sensor of passive detection, its measured data can be filtered to improve the guidance precision. Amid interference countermeasures, the measured data can be filtered to reduce noise, and the angular velocity and other information can be obtained to provide auxiliary factors for data fusion. In addition, under the collaborative tracking condition with only two-dimensional angle information, it can provide the target data time alignment method for triangulation so as to improve the positioning accuracy.
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Received: 01 June 2020
Published: 21 June 2021
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