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.
Dear editor,The source number and direction of arrival （DOA） estimation are two important subjects in array sig- nal processing [1,2]. Many algorithms for estimating these parameters have been proposed in the past decades [3-7]. The common approach for determining the source number is to use a certain informa- tion theoretic criterion [3,4] in an additive white Gaussian noise （AWGN） environment, e.g., the AIC and MDL criteria. Conventional DOA estimation algorithms can be roughly classified into two types, beamforming techniques and eigenstructure-based methods [4-7], such as the Capon, MUSIC and Root- MUSIC algorithms. In addition, the rnCapon method [5] has been proposed to improve the resolution performance of the Capon algorithm by using an adjustable power parameter rn.
Due to the low sound propagation speed, the tradeoff between high azimuth resolution and wide imaging swath has severely limited the application of sonar underwater target imaging. However, based on compressed sensing(CS) technique, it is feasible to image targets with merely one pulse and thus avoid the above tradeoff. To investigate the possible waveforms for CS-based underwater imaging, the deterministic M sequences widely used in sonar applications are introduced in this paper. By analyzing the compressive matrix constructed from M sequences, the coherence parameter and the restricted isometry property(RIP) of the matrix are derived. Also, the feasibility and advances of M sequence are demonstrated by being compared with the existing Alltop sequence in underwater CS imaging framework. Finally, the results of numerical simulations and a real experiment are provided to reveal the effectiveness of the proposed signal.
Huichen YANJia XUXiang-Gen XIAXudong ZHANGTeng LONG
