Elastic Characteristic Extraction Method of Underwater Target Based on Adaptive Filtering

In this paper, a kind of elastic characteristic extraction method of underwater targets based on adaptive filtering is introduced. The kernel of the method is the recursive least square （RLS） algorithm. Firstly, the geometric scattering signal is fit by using the echo signal and the incident signal. Then, the frequency spectrum of the echo signal and the geometric scattering signal are calculated. At last, the frequency spectrum of the elastic scattering signal is obtained. The research of the simulation and lake experiment is carried on. As the results show, the formants of the elastic signal frequency spectrum can be precisely extracted by the algorithm, and the extraction algorithm can apply to extracting the elastic characteristic from the echo signal in a real underwater acoustics environment.

Identification of Denatured Biological Tissues Based on Improved Variational Mode Decomposition and Autoregressive Model during HIFU Treatment

During high-intensity focused ultrasound(HIFU)treatment,the accurate identification of denatured biological tissue is an important practical problem.In this paper,a novel method based on the improved variational mode decomposition(IVMD)and autoregressive(AR)model was proposed,which identified denatured biological tissue according to the characteristics of ultrasonic scattered echo signals during HIFU treatment.Firstly,the IVMD method was proposed to solve the problem that the VMD reconstruction signal still has noise due to the limited number of intrinsic mode functions(IMF).The ultrasonic scattered echo signals were reconstructed by the IVMD to achieve denoising.Then,the AR model was introduced to improve the recognition rate of denatured biological tissues.The AR model order parameter was determined by the Akaike information criterion(AIC)and the characteristics of the AR coefficients were extracted.Finally,the optimal characteristics of the AR coefficients were selected according to the results of receiver operating characteristic(ROC).The experiments showed that the signal-to-noise ratio(SNR)and root mean square error(RMSE)of the reconstructed signal obtained by IVMD was better than those obtained by variational mode decomposition(VMD).The IVMD-AR method was applied to the actual ultrasonic scattered echo signals during HIFU treatment,and the support vectormachine(SVM)was used to identify the denatured biological tissue.The results show that compared with sample entropy,information entropy,and energy methods,the proposed IVMD-AR method can more effectively identify denatured biological tissue.The recognition rate of denatured biological tissue was higher,up to 93.0%.

Application of the direct blast adaptive suppression method to the forward scattered broadband signals

The basic principles of target detection by forward acoustic scattering are presented.A direct blast suppression approach based on adaptive filtering(DBS-AF) is proposed to suppress the direct blast.The DBS-AF technique is extended to the linear frequency modulation(LFM) signal,where the envelope of the signal is regarded as a 'general waveform' and imported into the adaptive filter.Application of the DBS-AF method to the data collected from a lake trial yields an output detection curve,in which the direct blast is mapped to the background while the acoustic field aberration is represented by the peak value fluctuation.The inhibitory effect in single hydrophone is approximately- 5 dB,and is then enhanced by exploiting the mean value removal approach as a preprocessing technique.The direct blast is further suppressed to a level of-10 dB by making full use of multichannel receptions.The main factors affecting the algorithm performance are as follows:the fluctuation degree of the receptions during the weighting vector training period and the power ratio of the forward scattered wave to the direct blast when the target is present.