Wind Speed And Direction Measurement Method Based On Co-prime Array

As an important natural phenomenon,wind is closely related to the production and life of human society.Accurate measurement of wind parameters plays an important role in aviation,navigation,industry,agriculture and environmental monitoring.The existing anemometers mainly include mechanical anemometers,thermal anemometers,laser Doppler anemometers,ultrasonic anemometers.Among them,ultrasonic anemometers are widely used due to their advantages of large measurement range,fast measurement speed and high sensitivity.The traditional ultrasonic anemometer mainly measures the wind speed according to time difference method.Therefore,the measurement accuracy of wind parameters is closely related to the TOF,in the low signal-to-noise ratio environment,the accuracy of TOF is seriously degraded,and the accurate measurement of wind parameters cannot be achieved.In view of the shortcomings of the current ultrasonic anemometers,this paper mainly designs a co-prime arc array structure to improve the space utilization of ultrasonic signals,increase the redundant information of wind signals,and then use the corresponding algorithm to achieve accurate measurement and prediction of wind parameters.The main innovations and main contents of this paper are as follows:1.A co-prime arc array structure is designed.Compared with the traditional uniform array structure,this structure has the advantages of expanding the array aperture and improving the estimation accuracy of wind parameters.Based on this array structure,the array manifold matrix of the co-prime arc array in the wind field environment is derived.2.Based on the co-prime arc array structure,the mathematical is established,and the measurement of wind speed and direction is realized by combining with the multiple signal classification algorithm(MUSIC).On this basis,a wind measurement algorithm based on the propagation method(PM)is proposed.Combined with the co-prime array,the wind measurement performance similar to the MUSIC algorithm,and more importantly,the calculation amount of the PM algorithm is reduced.Finally,combined with theoretical analysis and simulation experiments,the performance of wind parameters measurement based on the co-prime array is verified.3.Aiming at the problem that the above methods need to search for spectral peaks when estimating wind parameters,and the amount of calculation is large.A wind speed and direction measurement method based on PSO and ABC algorithm is deduced,and wind parameters estimation problem is transformed into a function optimization problem,and the fast and accurate measurement is realized.Simulation comparison experiment verify that the proposed method has good measurement performance,and the measurement time is one-sixth of the original method,which improves the real-time performance of the wind measurement system.Then,the particle swarm algorithm is improved to obtain a dynamic particle swarm algorithm,which further improves the estimation performance of wind parameters and realizes real-time tracking of wind speed and direction.4.Aiming at the problem of dynamic wind speed and direction measurement,a constant velocity(CV)model and a constant acceleration(CA)model suitable for wind speed and direction change are established.The mathematical model of wind speed and direction prediction is realized by extended Kalman filter and particle filter.Finally,a simulation comparison experiment is designed based on the proposed prediction method to verify that the proposed method can effectively monitor the changing wind conditions.