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Implementation of Adaptive and Synthetic-Aperture Processing Schemes in Integrated Active–Passive Sonar Systems

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Implementation of Adaptive and Synthetic-Aperture Processing Schemes in Integrated Active–Passive Sonar Systems Implementation of Adaptive and Synthetic-Aperture Processing Schemes in Integrated Active–Passive Sonar Systems STERGIOS STERGIOPOULOS, SENIOR MEMBER, IEEE Progress in the implementation of state-of-the-art signal- NOMENCLATURE processing schemes in sonar systems is limited mainly by the moderate advancements made in sonar computing architectures Complex conjugate transpose operator. and the lack of operational evaluation of the advanced processing Power spectral density of signal . schemes. Until recently, matrix-based processing techniques, such as adaptive and synthetic-aperture processing, could not AG Array gain. be efficiently implemented in the current type of sonar systems, Small positive number designed to main- even though it is widely believed that they have advantages that can address the requirements associated with the difficult tain stability in normalized least mean operational problems that next-generation sonars will have to square adaptive algorithm. solve. Interestingly, adaptive and synthetic-aperture techniques Narrow-band beam-power pattern of may be viewed by other disciplines as conventional schemes. For a line array expressed by the sonar technology discipline, however, they are considered as advanced schemes because of the very limited progress that has . been made in their implementation in sonar systems. Broad-band beam-power pattern of a line This paper is intended to address issues of implementation of array steered at direction . advanced processing schemes in sonar systems and also to serve as a brief overview to the principles and applications of advanced Beams for conventional or adaptive sonar signal processing. The main development reported in beam formers or plane wave this paper deals with the definition of a generic beam-forming response of a line array steered structure that allows the implementation of nonconventional at direction and expressed by signal-processing techniques in integrated active–passive sonar . systems. These schemes are adaptive and synthetic-aperture beam formers that have been shown experimentally to provide BW Signal bandwidth. improvements in array gain for signals embedded in partially Signal blocking matrix in generalized correlated noise fields. Using target tracking and localization side-lobe canceller adaptive algorithm. results as performance criteria, the impact and merits of these techniques are contrasted with those obtained using the Speed of sound in the underwater sea conventional beam former. environment. Keywords— Acoustic scattering, adaptive signal processing, CFAR Constant false alarm rate. beam steering, beams, covariance matrices, delay estimation, digital signal processors, estimation, FIR digital filters, Fourier Steering vector having its th phase transforms, frequency domain analysis, frequency estimation, term for the plane wave arrival with maximum likelihood estimation, multisensor systems, signal angle being expressed by detection, sonar signal processing, sonar tracking, spectral analysis, synthetic-aperture sonar, underwater acoustic arrays. Detection index of receiver operating characteristic curve. Sensor spacing for a line array receiver. Manuscript received May 15, 1996; revised September 1, 1997. This DT Detection threshold. work was supported in part by the Natural Sciences and Engineering Expectation operator. Research Council of Canada under NSERC Strategic Grant STR01810390 and NSERC Research Grant OGP0170406. ETAM Extended towed array measurements. The author is with the Defence and Civil Institute of Envi- Noise vector component with th ele- ronmental Medicine, North York, Ont. M3M 3B9 Canada (e-mail: [email protected]). ment for sensor outputs (i.e., Publisher Item Identifier S 0018-9219(98)01298-5. ). 0018–9219/98$10.00 1998 IEEE 358 PROCEEDINGS OF THE IEEE, VOL. 86, NO. 2, FEBRUARY 1998 Frequency in hertz. Power spectral density of noise, . Sampling frequency. S Source energy flux density at a range of GSC Generalized side-lobe canceller. 1 m from the acoustic source. Vector of weights for spatial shading in STCM Steered covariance matrix. beam-forming process. STMV Steered minimum variance. Unit vector of ones. SVD Singular value decomposition method. Index of time samples of hydrophone Time delay between the first and the time series . th hydrophone of the line array for an Iteration number of adaptation process. incoming plane wave with direction of Wave-number parameter. propagation . Size of line array expressed by Diagonal steering matrix with elements . those of the steering vector . Wavelength of acoustic signal with fre- TL Propagation loss for the range separating quency , where . the source and the sonar array receiver. LCMV Linearly constrained minimum variance. Angle of plane wave arrival with respect Number of time samples in to a line array receiver. hydrophone time series, where Adaptive steering vector. Frequency in rad/second. Convergence controlling parameter or “step size” for the normalized least mean Beam time series, output of time- square algorithm. domain beam former or formed by using MVDR Minimum variance distortionless re- fast Fourier transforms and fast convolu- sponse. tion of frequency-domain beam formers Number of hydrophones in line ar- IFFT . ray receiver, where Mean acoustic intensity of hydrophone . time sequences at frequency bin . Noise energy flux density at the receiv- Fourier transform of . ing array. Presteered hydrophone time series in fre- Index for space samples of hydrophone quency domain. time series . Row vector of received -hydrophone NLMS Normalized least mean square. time series . OMI Operator-machine interface. Presteered hydrophone time series in Probability of detection for receiver op- time domain. erating characteristic curves. Result of the signal blocking matrix C Probability of false alarm for receiver being applied to presteered hydrophone operating characteristic curves. time series . Steered spatial covariance matrix in time domain. I. INTRODUCTION 3.14 159. Several review articles [1]–[4] on sonar system technol- Spatial correlation matrix with elements ogy have provided a detailed description of the mainstream for received hydrophone sonar signal-processing functions along with the associ- time series. ated implementation considerations. This paper attempts to Cross-correlation coefficients given from extend the scope of these articles by introducing an imple- . mentation effort of nonmainstream processing schemes in real-time sonar systems. The organization of this paper is ROC Receiver operating characteristic curve. as follows. Spatial correlation matrix for the plane The first section provides a historical overview of sonar wave signal . systems and introduces the concept of the signal-processor Spatial correlation matrix for the unit and its general capabilities. This section also outlines plane wave signal in frequency the practical importance of the topics to be discussed domain. It has its th row and th in subsequent sections, defines the sonar problem, and column defined by provides an introduction into the organization of the paper. In Section II, we discuss very briefly a few issues Signal vector whose th element is ex- of space-time signal processing related to detection and pressed by . procedures for estimating sources’ parameters. Section III STERGIOPOULOS: IMPLEMENTATION OF PROCESSING SCHEMES 359 deals with optimum estimators for sonar signal processing. It introduces various nonconventional processing schemes (adaptive and synthetic-aperture beam formers) and the practical issues associated with the implementation of these advanced processing schemes in sonar systems. Our intent here is not to be exhaustive but only to be illustrative of how the receiving array, the underwater medium, and the subsequent signal processing influence the performance of a sonar system. Issues of practical importance, related to system-oriented applications, are also addressed, and generic approaches are suggested that could Fig. 1. Overview of a generic sonar system. It consists of a be considered for the development of next-generation sonar wet end, a high-speed signal processor to provide mainstream signal-processing concepts. These generic approaches are signal processing for detection and initial parameter estimation, a then applied to the central problem that the sonar systems data manager, which supports the data and information processing functionality of the system, and a display subsystem through which deal with, that is, detection and estimation. the system operator can interact with the manager to make the most Section IV introduces the development of a realizable effective use of the information available at his command. generic processing scheme that allows the implementa- tion and testing of nonlinear processing techniques in a wide spectrum of real-time sonar systems. The comput- underwater acoustic signal. These devices are hydrophone ing architecture requirements for future sonar systems are arrays having cylindrical, spherical, plane, or line geometric addressed in the same section. It identifies the matrix configurations that are housed inside domes of naval ships operations associated with high-resolution and adaptive or towed at a depth behind a vessel. Quantitative estimates signal processing and discusses their numerical stability of the various benefits that result from the deployment of and implementation requirements. The mapping onto sonar arrays of hydrophones are obtained by the array gain term, signal processors of matrix operations includes
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