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In this paper, we propose a new maximum-likelihood (ML) target localization approach which uses quantized sensor data as well as wireless channel statistics in a wireless sensor network. The novelty of our approach comes from the fact that statistics of imperfect wireless channels between sensors and the fusion center along with some physical layer design(More)
Wireless Sensor Networks (WSNs) are vulnerable to Byzantine attacks in which malicious sensors send falsified information to the Fusion Center (FC) with the goal of degrading inference performance. In this paper, we consider Byzantine attacks for the location estimation task in WSNs using binary quantized data. Posterior Cramér-Rao Lower Bound(More)
In this paper, a new framework for target tracking in a wireless sensor network using particle filters is proposed. Under this framework, the imperfect nature of the wireless communication channels between sensors and the fusion center along with some physical layer design parameters of the network are incorporated in the tracking algorithm based on(More)
—The recursive procedure to compute the posterior Cramér-Rao lower bound (PCRLB) for sequential Bayesian estima-tors, derived by Tichavsky et al., provides an off-line performance bound for a general nonlinear filtering problem. Since the corresponding Fisher information matrix (FIM) is obtained by taking the expectation with respect to all the random(More)
—The performance of a modulation classifier is highly sensitive to channel signal-to-noise ratio (SNR). In this paper, we focus on amplitude-phase modulations and propose a modulation classification framework based on centralized data fusion using multiple radios and the hybrid maximum likelihood (ML) approach. In order to alleviate the computational(More)
We propose a modified Bayesian Cramér-Rao lower bound (BCRLB) for nonlinear tracking applications where the prediction distribution conditioned on past measurements is used as the prior. The novelty of the proposed modified BCRLB comes from the fact that it utilizes past measurements, therefore it is specific to the current realization of the track(More)
In this article, we design a novel energy-detection based receiver architecture to detect UWB signals in a strong narrowband interference (NBI) environment. Designed receiver is capable of suppressing NBI at low cost without any need for searching its frequency location. This is made possible by preprocessing the received signal using a cascaded nonlinear(More)
We address the problem of discovering unknown digital amplitude-phase modulations over block-fading additive noise channels. The proposed method uses the iterative Richardson-Lucy algorithm to determine the distribution of the transmitted symbols, which completely characterizes the underlying signal constellation. The decoding of the received signals can(More)
In this paper, we propose a Byzantine identification scheme for a target localization scenario in wireless sensor networks (WSN) with binary quantized observations. We first start with identical quantizers at the local sensors. We show with simulations that the proposed scheme identifies `almost' all the Byzantines present in the network. Then, in order to(More)