Research On Communication Signals Processing With Multiple Sensors

In the process of wireless communication,multipath effect and Doppler effect causes serious distortion on the received signals.Receiving with multiple sensors could get different quality signals in different location,improve the quality of received signals,and improve the SNRs,reduce the influence of channel fading.Underwater Acoustic?UWA?communication is a kind of wireless communication used in underwater,and is important for ocean development and national defense construction.UWA channel exhibit both dispersion in time?delay spread?and frequency?Doppler spread?,sparsity in time and frequency domin,non uniform sound speed and so on,resulting in great challenage in UWA communication.Thus,we start from the receive form of the signal,the characteristic of channel and signal,base on multiple sensors,focus on the problem of modulation classification of communication signals,blind equalization of UWA sparse time varying?TV?SIMO channel,and non-uniform Doppler estimate of TV multipath UWA channel.The main works and achievements proposed in this paper are summarized as follows.Firstly,aiming at the problem of modulation classification of communication signals with multiple sensors,we proposed a feature vector based maximum likelihood algorithm with multiple sensors based on the system model of multiple sensors.Recognition features is chosen and its distribution is approximated,the feature vector is constructed.The feature vector based likelihood fuction is constructed for modulation classification.Simulation results demonstrate that the proposed algorithm can directly process the over-sampled signals in medium frequency,effectively improve the performance of the existing algorithm in low SNRs,and is more practical.Secondly,aiming at the problem of blind equalization of UWA sparse TV SIMO channel,we proposed a modified blind equalization algorithm for UWA sparse TV SIMO channel.We use complex exponential basis expansion model?CE-BEM?to describe the UWA channel.Taking advantage of the sparsity of the channel and the constant modulus?CM?characteristics of the signals,we design a SIMO equalizer.Firstly,using the ₀l-norm constraint improved proportionate normalized least mean square constant modulus algorithm?l₀-IPNLMS-CMA?to equalize the sparse time-invariant?TIV?part of channel matrix,then using the extended basis frequency estimation method to compensate the Doppler shifts,finally,estimate and compensate the phase offset in the recovered signals.Simulation results demonstrate that the proposed algorithms improve the performance,and the Bellhop based experiments test the effectiveness of the proposed algorithm.Moreover,we give the design and realize scheme of the distortion compensation process platform for UWA multipath TV nolinear channel.Finally,aiming at the problem of non-uniform Doppler estimate of TV multipath UWA channel,we proposed a compress sensing based non-uniform Doppler estimate algorithm.Taking advantage of the time-frequency domain sparsity characteristic of UWA channel,the non-uniform Doppler expand estimation is equivalent to a sparse reconstruction problem.Considering UWA channel is timevarying,choose the low complexity high stability Subspace Pursuit?SP?algorithm to solve it.Simulation results show that the proposed method can process the band-pass over-sampled UWA signal directly,estimate the the non-uniform Doppler extend exactly with short sampling time and high noise immunity,and is especially suitable for high-speed mobile UWA communication.Time Variable Acoustic Propagation Model?TV-APM?based results show that the proposed method perform better without wind on the sea surface.