Energy-Based Acoustic Source Localization Methods: A Survey <s> Quantized Signal Energy <s> A signal intensity based maximum-likelihood (ML) target location estimator that uses quantized data is proposed for wireless sensor networks (WSNs). The signal intensity received at local sensors is assumed to be inversely proportional to the square of the distance from the target. The ML estimator and its corresponding Crameacuter-Rao lower bound (CRLB) are derived. Simulation results show that this estimator is much more accurate than the heuristic weighted average methods, and it can reach the CRLB even with a relatively small amount of data. In addition, the optimal design method for quantization thresholds, as well as two heuristic design methods, are presented. The heuristic design methods, which require minimum prior information about the system, prove to be very robust under various situations <s> BIB001 </s> Energy-Based Acoustic Source Localization Methods: A Survey <s> Quantized Signal Energy <s> We consider energy-based source localization applications, where distributed sensors quantize acoustic signal energy readings and transmit quantized data to a fusion node, which then produces an estimate of the source location. We propose an iterative quantizer design algorithm that allows us to take into account localization accuracy for quantizer design in the framework of the generalized Lloyd algorithm. Since source coding methodologies based on the Lloyd algorithm suffer from the presence of numerous poor local optima depending on initialization of quantizers, we introduce an efficient initialization, the equally distance-divided quantizer (EDQ), designed so that quantizer partitions correspond to a uniform partitioning in terms of distance. Our simulations demonstrate that improved performance over traditional quantizer designs can be achieved by using our proposed application specific strategy. <s> BIB002 </s> Energy-Based Acoustic Source Localization Methods: A Survey <s> Quantized Signal Energy <s> Wireless Sensor Networks (WSNs) are vulnerable to Byzantine attacks in which malicious sensors send wrong data to the fusion center leading to an increase in the probability of incorrect inference. This paper considers Byzantine attacks for the location estimation task in wireless sensor networks where each sensor uses a binary quantization scheme to send binary data to the fusion center. Posterior Cramer-Rao lower Bound (PCRLB) metric and Fisher Information Matrix (FIM) are used to analyze the performance of the network in the presence of Byzantine attacks. We have considered two kinds of attack strategies, independent attacks (all the malicious sensors attack a WSN independently of each other) and collaborative attacks (all the malicious sensors communicate with each other and attack the WSN in a coordinated manner). We determine the fraction of Byzantine attackers in the network above which the fusion center becomes incapable of finding the location of the target. Optimal attacking strategy for given attacking resources is also proposed. <s> BIB003
For practical systems, it will require the quantization of the measurements before transmission. In BIB002 BIB001 BIB003 , source localization using the quantized sensor signal energy readings was considered. Different quantization strategies, e.g., equally distance-divided quantizer (EDQ) BIB002 , were proposed for energy-aware source localization. In BIB001 , two heuristic quantization design methods were proposed from maximum-likelihood (ML) target localization. In BIB003 , the authors consider Byzantine attacks for the location estimation task where each sensor uses a binary quantization scheme to send binary data to the fusion center. In these target localization methods with quantized signal energy, the location estimators adopt simple or improved grid search strategies.