Bionic covert anti-reverberation active sonar detection method based on imitating whale whistles

The disguised covert detection method that imitates whale calls has received great attention in recent years because it can solve the traditional problem of the trade-off between long-range detection and covert detection.However,under strong reverberation conditions,traditional echo signal processing methods based on matched filtering will be greatly disturbed.Based on this,a disguised sonar signal waveform design is proposed based on imitating whale calls and computationally efficient anti-reverberation echo signal processing method.Firstly,this article proposed a disguised sonar signal waveform design method based on imitating whale calls.This method uses linear frequency modulation(LFM)signals to replace LFM-like segments in real whale calls,and extracts the envelope of the real whale call’s LFM-like segment to modify the LFM signal.Secondly,this article proposed an echo signal processing method of fractional Fourier transform(FrFT)based on target echo locating of synchronization signals.This method uses the synchronization signal to locate the target echo,and determines the step-size interval of the FrFT based on the information carried by the synchronization signal.Compared with the traditional FrFT,this method effectively reduces the amount of calculation and also improves the anti-reverberation ability.Finally,the excellent performance of the proposed method is verified by simulation results.

Research on strong reverberation suppression for high resolution active sonar

Resolution enhancement of active sonar can suppress the reverberation.While it also makes the envelope data distribution diverge from Rayleigh distribution to K-distribution.The stronger scattering speckles,the heavier of the K-distribution tails.The envelope amplitudes of these strong scattering speckles are usually very big.As the interfering target,the strong reverberation decreases the performances of the background power level estimation and the target detection.The fuzzy statistical normalization processing(FSNP) is introduced to suppress the strong reverberation firstly in this paper.Then how the strong reverberation and the FSNP affect the distribution of K-distributed sonar data is studied.The influence on the constant false alarm rate(CFAR) detection performance caused by the strong reverberation and the FSNP is also simulated and analyzed.Performance comparisons between the CFAR detector based on FSNP and the conventional CFAR detectors are carried out.The simulation results show that the strong reverberation can make the shape parameter of the interfering K-distributed data become smaller than that of the original K-distributed data.While the FSNP can suppress the strong reverberation,increase the shape parameter value,and improve the performance of the shape parameter estimator and the CFAR detector.

A tracking filter method of active sonar subject to unknown target maneuver

A tracking filter algorithm based on the maneuvering detection delay is presented in order to solve the fuzzy problem of target maneuver decision introduced by the measure？ment errors of active sonar. When the maneuvering detection is unclear, two target moving hypotheses, the uniform and the maneuver, derived from the method of multiple hypothesis tracking, are generated to delay the final decision time. Then the hypothesis test statistics is constructed by using the residual sequence. The active sonar？s tracking ability of unknown prior information targets is improved due to the modified sequential probability ratio test and the integration of the advantages of strong tracking filter and the Kalman filter. Simulation results show that the algorithm is able to not only track the uniform targets accurately, but also track the maneuvering targets steadily. The effectiveness of the algorithm for real underwater acoustic targets is further verified by the sea trial data processing results.