IMPROVED SYNTHETIC APERTURE SONAR MOTION COMPENSATION COMBINED DPCA WITH SUB-APERTURE IMAGE CORRELATION

Estimation precision of Displaced Phase Center Algorithm(DPCA) is affected by the number of displaced phase center pairs,the bandwidth of transmitting signal and many other factors.Detailed analysis is made on DPCA's estimation precision.Analysis results show that the directional vector estimation precision of DPCA is low,which will produce accumulating errors when phase cen-ters' track is estimated.Because of this reason,DPCA suffers from accumulating errors seriously.To overcome this problem,a method combining DPCA with Sub Aperture Image Correlation(SAIC) is presented.Large synthetic aperture is divided into sub-apertures.Micro errors in sub-aperture are estimated by DPCA and compensated to raw echo data.Bulk errors between sub-apertures are esti-mated by SAIC and compensated directly to sub-aperture images.After that,sub-aperture images are directly used to generate ultimate SAS image.The method is applied to the lake-trial dataset of a 20 kHz SAS prototype system.Results show the method can successfully remove the accumulating error and produce a better SAS image.

An Efficient Acoustic Scattering Model Based on Target Surface Statistical Descriptors for Synthetic Aperture Sonar Systems

Acoustic scattering as the perturbation of an incident acoustic field from an arbitrary object is a critical part of the targetrecognition process in synthetic aperture sonar(SAS)systems.The complexity of scattering models strongly depends on the size and structure of the scattered surface.In accurate scattering models including numerical models,the computational cost significantly increases with the object complexity.In this paper,an efficient model is proposed to calculate the acoustic scattering from underwater objects with less computational cost and time compared with numerical models,especially in 3D space.The proposed model,called texture element method(TEM),uses statistical and structural information of the target surface texture by employing non-uniform elements described with local binary pattern(LBP)descriptors by solving the Helmholtz integral equation.The proposed model is compared with two other well-known models,one numerical and other analytical,and the results show excellent agreement between them while the proposed model requires fewer elements.This demonstrates the ability of the proposed model to work with arbitrary targets in different SAS systems with better computational time and cost,enabling the proposed model to be applied in real environment.

A motion compensation method for wide-swath synthetic aperture sonar

When the swath of Synthetic Aperture Sonar（SAS） is considerably wide, the spacevariant effect of motion errors becomes remarkable. This space-variant effect makes Displace Phase Center Algorithm（DPCA） invalid. To solve the problem, a motion compensation method for wide-swath SAS is proposed. This method uses mixed modulated Lagrange explicit time delay estimation（MMLETDE） to estimate the time delay between two successive pings of the raw echo data, and then motion errors are fitted by linear regression. After that, the raw echo data can be precisely compensated point by point with the estimations of motion errors.Simulation results show that the proposed method can obtain better motion estimation results than DPCA. The resolution measured on the reconstructed image processed by the proposed method is very close to the theoretical resolution. The lake trail results of high frequency and low frequency SAS data show that the quality of the images of the terrain area and small targets is significantly improved.

Synthetic aperture sonar movement compensation algorithm based on time-delay and phase estimation

The effects of movement errors on imaging results of synthetic aperture sonar and the necessity of movement compensation are discussed. Based on analyzing so-called displaced phase center algorithm, an improved algorithm is proposed. In this method, the time delay is estimated firstly, then the phase is estimated for the residual error, so that the range of movement error suited to the algorithm is extended to some extent. Some simulation results on computer and experimental results in the test tank using the proposed algorithm are given as well.

Automatic target recognition method for inverse synthetic aperture sonar imaging

To address the randomness of target aspect angle and the incompleteness of observed target in inverse synthetic aperture sonar（ISAS） imaging,a method for target recognition is proposed based on topology vector feature（TVF） of multiple highlights. Analysis of the projection relationship from 3 D space to 2 D imaging plane in ISAS indicates that the distance between two highlights in the cross-range scale calibrated image is determined by the distance between the corresponding physical scattering centers. Then, TVFs of different targets, which remain stable in various possibilities of target aspect angle, can be built. K-means clustering technique is used to effectively alleviate effect of the point missing due to incompleteness of the observed target. A nearest neighbor classifier is used to realize the target recognition. The ISAS experimental results using underwater scaled models are provided to demonstrate the effectiveness of the proposed method. A classification rate of 84.0% is reached.

A simulation method on target strength and circular SAS imaging of Xrudder UUV including multiple acoustic scattering

Target strength(TS)and circular synthetic aperture sonar(CSAS)images provide essential information for active acoustic detection and recognition of non-cooperative unmanned undersea vehicles(UUVs),which pose a significant threat to underwater preset facilities.To access them,we propose an iterative physical acoustics(IPA)-based method to simulate the multiple acoustic scattered fields on rigid surfaces in high-frequency cases.It uses the Helmholtz integral equation with an appropriate Green's function in terms of the Neumann series,and then incorporates the ideas of triangulation and iteration into a numerical implementation.Then two approximate analytic formulae with precise physical meanings are derived to predict the TS and CSAS images of concave targets,respectively.There are no restrictions on the surface's curvature and the order of multiple scattering.The method is validated against the finite element method(FEM)for acoustic scattering from a sphere segment and against an experiment involving an X-rudder UUV's stern.On this basis,we simulate and analyze the TS and CSAS images of an X-rudder UUV.In addition,the influence of the angle of adjacent rudders on the multiple scattering characteristics is discussed.Results show that this method can potentially predict accurate UUV features,especially the multiple scattered features.