Localization of wide-band signals via extended Kalman filter

Using Fourier transformation and causality theorem, we proposed a new set of equations which are applicable to the localization of wide-band multiple sources. We presented necessary conditions for the unique localization in terms of sensor number, source number and the rank of the signal covariance matrix. In this paper, we propose a FFT-based algorithm for the localization of wide-band acoustic signals via extended Kalman filter(EKF). The algorithms is developed for the localization of signals using the clustered passive sensor arrays with acoustic and meteorological (temperature and pressure) sensors. The simulation results and the robustness of the algorithm against the noisy conditions such as wind are presented. The presented method is also an alternative proof in handling wide-band signals instead of narrowband signals which have known center frequency.