Multi-path Channel Association And Filtering Technique For Underwater Acoustic

Due to the narrow available bandwidth and strong noise of the underwater acoustic signal,it has obvious multi-path effect,so that the traditional maximum energy criterion cannot accurately track the direct path,thus affecting the performance of underwater acoustic communication.In order to accurately and stably track the direct path from the clutter and multi-channel channels,this paper draws on the multi-target tracking technology in the radar field,and uses the time correlation between the adjacent symbols of the direct spread communication to distinguish and track the channel as multiple targets,and studies whether the method can be applied to the field of underwater acoustic channel tracking.Under the condition of low signal-to-noise ratio,multiple correlation peaks are obtained through signal preprocessing.In this paper,the nearest neighbor(NN)algorithm,the joint probabilistic data association(JPDA)algorithm and the multiple hypothesis tracking(MHT)algorithm are used to determine the correlation peaks.The model selection,noise parameter setting and channel initialization problems encountered in correlation and filtering are solved through simulation.In this paper,three kinds of underwater acoustic channel models are combined with corresponding filtering algorithms to conduct in-depth research.The constant velocity(CV)and constant acceleration(CA)models are filtered by the Kalman filter(KF)algorithm,and the complex model is filtered by the extended Kalman filter(EKF)algorithm and unscented Kalman filter(UKF)algorithms.Through the simulation analysis of different channel scenarios,it is found that the CA model can be applied to the underwater acoustic channel tracking in general scenarios.For the problem of noise parameter setting,the measurement noise parameters are set by using the accuracy of three-point interpolation estimation.It is found through simulation that when the SNR is low,the process noise is set to the same magnitude as the measurement noise,which can ensure high tracking accuracy and avoid the mismatching of noise parameters.Under the condition of low signal-to-noise ratio,after the NN algorithm and MHT algorithm combined with the channel initiation algorithm to obtain more accurate channel initialization parameters,compared with the traditional maximum energy criterion,the channel can still be accurately distinguished within the 3d B range of its failure,the tracking performance of the MHT algorithm is slightly better than that of the NN algorithm.However,the JPDA algorithm cannot effectively suppress clutter due to the inherent nature of the algorithm and the influence of tracking accuracy.For the case of channel Doppler and amplitude dynamic changes,the two above-mentioned NN algorithms and MHT algorithms that can distinguish the channel in clutter are studied.It can better track the channel in the process of slow change;for the case of Doppler mutation,the performance of both algorithms suddenly deteriorates during the mutation period,and can only reconverge after a period of time.For the situation that the number of channels changes dynamically due to the extreme change of amplitude,this paper adopts the channel number management technology to judge the start and end of the channel.When the channel amplitude changes dynamically,both the NN algorithm and the MHT algorithm can track the channel better.Under the simulation conditions with good channel environment,the tracking performance of the NN algorithm is close to that of the MHT algorithm,but the calculation amount of the MHT algorithm is much larger than that of the NN algorithm,the real-time performance is poor,so for the actual underwater acoustic experimental data processing,the NN algorithm can be selected to obtain better channel tracking performance.In this paper,through two common scenarios in underwater acoustic experiments with low signal-to-noise ratio and channel dynamic change,aiming at the failure of the maximum energy criterion,it is found that the NN algorithm is suitable for the experimental data processing in the above two cases,and finally verified by the lake test data.The channel speed tracked by the receiver combined with the NN algorithm is smoother,and is within 15cm/s of the GPS measurement speed;using the channel delay parameter tracking result to obtain the signal phase for hard decision can solve the problem of decoding the phase obtained by the traditional method to a certain extent.In addition,using the channel speed tracked by the NN algorithm to make soft decisions can achieve higher communication performance.