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 (CRB) 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.

Since publication of the first edition of Sensor Array Signal Processing in 2000, the field it heralded has come of age. Sensor arrays helped usher in the age of wireless communication by meeting the increasing capacity requirements of ever growing wireless networks, but that is only one example of the number of uses served by this valuable te

The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sensor Networks, Second Edition once again provides all the fundamentals and applications in one complete, self-contained source. Ideal as a tutorial for

Discusses localization in 2D and 3D space Includes random and sparse sensor distribution Provides effective algorithms and illustrative numerical examples Concepts are described in detailed mathematical form Contains simple lab experiments

A handbook on recent advancements and the state of the art in array processing and sensor Networks Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks. Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks. Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.

The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sensor Networks, Second Edition once again provides all the fundamentals and applications in one complete, self-contained source. Ideal as a tutorial for

Sensors arrays are used in diverse applications across a broad range of disciplines. Regardless of the application, however, the tools of sensor array signal processing remain the same. Furthermore, whether your interest is in acoustic, seismic, mechanical, or electromagnetic wavefields, they all have a common mathematical framework. Mastering this