Abstract
The compressive time delay estimation (TDE) is combined with delay-and-sum beamforming to obtain direction-of-arrival (DOA) estimates in the time domain. Generally, the matched filter that detects the arrivals at the hydrophone is used with beamforming. However, when the ocean noise smears the arrivals, ambiguities appear in the beamforming results, degrading the DOA estimation. In this work, compressive sensing (CS) is applied to accurately evaluate the arrivals by suppressing the noise, which enables the correct detection of arrivals. For this purpose, CS is used in two steps. First, the candidate time delays for the actual arrivals are calculated in the continuous time domain using a grid-free CS. Then, the dominant arrivals constituting the received signal are selected by a conventional CS using the time delays in the discrete time domain. Basically, the compressive TDE is used with a single measurement. To further reduce the noise, common arrivals over multiple measurements, which are obtained using the extended compressive TDE, are exploited. The delay-and-sum beamforming technique using refined arrival estimates provides more pronounced DOAs. The proposed scheme is applied to shallow-water acoustic variability experiment 15 (SAVEX15) measurement data to demonstrate its validity.
Highlights
To detect a target signal, the sonar system uses an array that consists of multiple hydrophones, enabling target localization via direction-of-arrival (DOA) detection
The time domain beamforming with compressive sensing (CS) was applied to the shallow-water acoustic variability experiment 15 (SAVEX15) experimental data, which were gathered in the northeastern East China Sea [23,24]
The compressive sensing (CS) technique was applied for the extraction of the channel impulse responses (CIRs) along the ocean depths
Summary
To detect a target signal, the sonar system (equivalent to the radar system in the air) uses an array that consists of multiple hydrophones, enabling target localization via direction-of-arrival (DOA) detection. DOA results owing to the limited number of sensors in the array. To overcome this problem, adaptive beamforming schemes, such as minimum variance distortionless response (MVDR) [1,2] and multiple signal classification (MUSIC) [1,3], are applied. Adaptive beamforming schemes, such as minimum variance distortionless response (MVDR) [1,2] and multiple signal classification (MUSIC) [1,3], are applied Their applications are restricted by insufficient measurement data as well as coherent arrivals that typically exist underwater
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