Detection of Array Signal Number With Multiple Sensors Based on Transfer Component Analysis

The conventional algorithms for estimating number of array signals are only suitable for the background of Gaussian white noise, and need many snapshots, but their performance will reduce seriously in the circumstance of impulse noise and small samples. Therefore, a new method of detecting array signal number with multiple sensors based on transfer component analysis is proposed in this paper. First, the array signals in Gaussian white and impulse noise are respectively modeled. Then the received array data are transformed into a common hidden space by the mapping function, thus, data in the hidden space have the same distribution, and most initial characteristics are retained. Finally, a support vector machine or K-means clustering are used for classifying the mapped data into two categories, on this basis, the array signal number can be estimated.