Data processing algorithm of coherent wind measurement based on time domain alignment

• Published in: Scientific Bulletin. Series C, Electrical Engineering and Computer Science no. 2; p. 153
• Main Authors: Wang, Zhendong, Hou, Zaihong, Jing, Xu
• Format: Journal Article
• Language: English
• Published: Bucharest University Polytechnica of Bucharest 01.01.2025
• Subjects: Accumulation; Algorithms; Alignment; Coherence; Correlation coefficients; Data processing; Lidar; Phase relationships; Random noise; Signal detection; Wind measurement; Wind speed
• ISSN: 2286-3540

The signal - to - noise ratio (SNR) is a crucial factor influencing the performance of coherent wind lidar. The interference of random noise can be mitigated through the accumulation of multiple pulses. Non - coherent accumulation simply accumulates signals without taking into account their phase relationships. In contrast, a coherent accumulation algorithm, which makes use of the signal's phase information to achieve in - phase superposition of the signal, can more effectively optimize the signal - to - noise ratio. This paper proposes a coherent accumulation algorithm based on time - domain alignment. This algorithm employs correlation coefficients to match and compensate for the modulation of pulse signals, thereby achieving coherence among echoes. Subsequently, accumulation averaging is carried out to obtain an SNR gain. Numerical simulations are performed to evaluate the algorithm's detection ability for echo signals under different amplitude noise interferences. When compared with non - coherent accumulation and direct coherent accumulation algorithms, the proposed algorithm can significantly enhance the signal detection probability. In actual detections, by comparing non - coherent accumulation and direct coherent accumulation algorithms using the radial wind speeds in actual fixed atmospheric regions, the accuracy of real - time signal detection can be optimized. In low - power detections, the algorithm can extract wind speed information with fewer pulse accumulations. Moreover, by combining multiple sets of wind speed data, it can clearly analyze the probability distribution of wind speeds. The algorithm enables the calculation of simulated wind speeds and the radial wind speeds at fixed atmospheric points and can be effectively applied to the data processing of atmospheric wind fields measured by coherent wind lidar.