Abstract: Based on the spatial virtual tapped-delay-line technique, the concept of spatiotemporal co- variance matrix (STCM) was introduced. At the same time, the concept of projection of eigenvectors of the array covariance matrix onto column-vectors of the STCM was also discussed. The two ap?proaches, based on Bootstrap and heuristic algorithms, were proposed for developing source number detection methods. The Like Gerschgoin disk estimator (GDE) method was proposed by the projec-tions of eigenvectors and the heuristic algorithm. It avoids the drawback of the existing source number detection methods based on eigenvalues, can work in the case of lower signal- to- noise ratio (SNR) and unknown spatially nonuniform noise. As no assumption is made on the distribution of the noise or the signals, another source number detection method was proposed by the projections of eigenvectors and the Bootstrap algorithm. In the latter method, no subjective detection threshold is required. The ex?periments with data from computer simulations as well as lake trials show that proposed methods are effective and superior to existing methods in different scenarios.

Key words: basic disciplines oi information science and system science , source number detection , spa?tial virtual tapped-delay-line , space-time projection of eigenvector , Bootstrap algorithm