Time reversal: Algorithms for M-ary target classification using array signal processing

An M-ary time reversal (TR) maximum likelihood classifier for a single pair oftransmitting and receiving transducer element was derived in [1] for underwater acoustic target detection applications. This paper considers a more general TR setup consisting of a P-element transmitting array and an N element receiving array and derives the M-ary conventional and TR classifiers for the multielement case in an electromagnetic communication environment. We show that the TR algorithm provides a classification gain ofover 3 dB at low signal to noise ratios as compared to the conventional classifiers. 1

N-Ary Maximum Likelihood Target Detection With Time Reversal

Atimereversal(TR)devicehasthecapabilityofreceivingatime varying signal, saving it in memory, and retransmitting the stored signal back into the medium in the reversed direction of time. The paper designs an N-ary maximum likelihood TR detector capable of detecting the presence of a target and classifying the detected target as an unknown enemy target or one of the (N − 2) known friendly targets. In our experiments, the proposed N-ary TR detector provides a gain of over 5dB over conventional detectors at low signal to noise ratios (SNR)

Wave atom based Compressive Sensing and adaptive beamforming in ultrasound imaging

The paper investigates combining Compressive Sensing (CS) with the robust Capon beamformer (RCB) for the purpose of medical ultrasound image formation with a much reduced number of samples compared to those used in current state-of-art ultrasound. The proposed CS algorithm uses wave atom dictionary as a low dimension projection, a Bernouli random matrix as a sensing matrix and a regularized-l1 optimization technique for recovery. The reconstructed signals are then pre-processed before using the RCB technique augmented with spatial smoothing and diagonal loading. This approach is demonstrated through simulations, wire phantom and in vivo cardiac data with a reduction of up to 1/8 in the processed data rate and ultrasound images of similar perceived quality

Super-resolution ultrawideband ultrasound imaging using focused frequency time reversal music

We propose a super-resolution image reconstruction method which uses focused frequency time reversal (FFTR) matrices to focus in frequency for ultrawideband (UWB) ultrasound signals, as well as time reversal MUltiple SIgnal Classification (MUSIC) algorithm to focus spatially on the target location. Our combined method, which we refer to as FFTR-MUSIC, is motivated by the pressing need to improve the resolution of diagnostic ultrasound systems. Compared with the TR matched filter (TRMF) and incoherent TR-MUSIC approaches, our proposed method has lower computational complexity, higher visibility, higher robustness against noise, and higher accuracy for imaging point targets when the targets are closely located. Our simulation results show that under mild speckle and noise conditions, the FFTR-MUSIC can resolve objects less than 200 μm

TIME REVERSAL MIMO RADAR: IMPROVED CRB AND ANGULAR RESOLUTION LIMIT

The paper derives closed form (nonmatrix) expression for the deterministic Cramér-Rao bound (CRB) for the direction-of-arrival associated with a target embedded in a noisy, multipath channel using the time reversal (TR) MIMO system. By incorporating the TR built-in adaptive waveform processing feature to reshape the MIMO probing signals, we prove that the CRBs for the direction of arrival can be improved in ways not foreseen with the conventional MIMO radars. Asecondcontributionofthepaperistheanalyticalderivation of the Angular Resolution Limit (ARL) defined as the minimal separation between two targets to be separately resolved by the MIMO radar. At high signal-to-noise ratio, we show that the TR ARL inherits the properties of the TR CRB and is superior to its conventional counterpart by a factor proportional to the order of the channel multipath. Index Terms — Time Reversal, MIMO radar, CRB and ARL. 1