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| Adaptive Signal Fusion Algorithm Based on Relative Fluctuation |
| PAN Zuo-zhou, MENG Zong, ZHANG Guang-ya, SHI Ying, FAN Feng-jie |
| Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract An improved adaptive random weighting algorithm was proposed to solve the problem that in the traditional random weighting algorithm, when the target signal is variable, the total mean square error is much larger than the constant signal. In order to make the estimated value closer to the true value, the mentioned algorithm used the relative fluctuation value of the collected signal to adaptively adjust the proportional relationship between the currently acquired signal and the historically acquired signal. Since the relative fluctuation value can be adjusted autonomously according to the signal variation, it can be well combined with the traditional random weighting algorithm. The effectiveness of the proposed fusion method had been demonstrated by numerical simulations.
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Received: 08 July 2019
Published: 23 June 2021
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2021, Vol. 42 
