Source localization with distributed sensor arrays and partial spatial coherence

We present performance analysis for source localization when wideband aeroacoustic signals are measured at multiple distributed sensor arrays. The acoustic wavefronts are modeled with perfect spatial coherence over individual arrays and with frequency-selective coherence between distinct arrays, thus allowing for random fluctuations due to the propagation medium when the arrays are widely separated. The signals received by the sensors are modeled as wideband Gaussian random processes, and we study the Cramer-Rao bound on source localization accuracy for varying levels of signal coherence between the arrays and for processing schemes with different levels of complexity. When the wavefronts at distributed arrays exhibit partial coherence, we show that the source localization accuracy is significantly improved if the coherence is exploited in the source localization processing. Further, we show that a distributed processing scheme involving bearing estimation at the individual arrays and time-delay estimation between pairs of sensors performs nearly as well as the optimum scheme that jointly processes the data from all sensors. We discuss tradeoffs between source localization accuracy and the bandwidth required to communicate data from the individual arrays to a central fusion center, and results from measured aeroacoustic data are included to illustrate partial spatial coherence at distributed arrays.