Rank determination in time-series analysis
ICASSP '94 Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04
On rank of block Hankel matrix for 2-D frequency detection andestimation
IEEE Transactions on Signal Processing
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This paper presents a new algorithm called Signal Subspace Extraction (SSE) for detecting and estimating target echoes in reverberation. The new algorithm can be taken as an extension of the Principal Component Inverse (PCI) and maintains the benefit of PCI algorithm and moreover shows better performance due to a more reasonable reverberation model. In the SSE approach, a best low-rank estimate of a target echo is extracted by decomposing the returns into short duration subintervals and by invoking the Eckart-Young theorem twice. It was assumed that CW is less efficiency in lower Doppler than broadband waveforms in spectrum methods; however, the subspace methods show good performance in detection whatever the respective Doppler is. Hence, the signal emitted by active sonar is CWin the new algorithm which performs well in detection and estimation even when low Doppler is low. Further, a block forward matrix is proposed to extend the algorithm to the sensor array problem. The comparison among the block forwardmatrix, the conventional matrix, and the three-mode array is discussed. Echo separation is also provided by the new algorithm. Examples are presented using both real, active-sonar data and simulated data.