On the calibration of the 3/2 model

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Distributed Algorithms for Stochastic Source Seeking With Mobile Robot Networks

Autonomous robot networks are an effective tool for monitoring large-scale environmental fields. This paper proposes distributed control strategies for localizing the source of a noisy signal, which could represent a physical quantity of interest such as magnetic force, heat, radio signal, or chemical concentration. We develop algorithms specific to two scenarios: one in which the sensors have a precise model of the signal formation process and one in which a signal model is not available. In the model-free scenario, a team of sensors is used to follow a stochastic gradient of the signal field. Our approach is distributed, robust to deformations in the group geometry, does not necessitate global localization, and is guaranteed to lead the sensors to a neighborhood of a local maximum of the field. In the model-based scenario, the sensors follow a stochastic gradient of the mutual information (MI) between their expected measurements and the expected source location in a distributed manner. The performance is demonstrated in simulation using a robot sensor network to localize the source of a wireless radio signal

SPSA-Based Tracking Method for Single-Channel-Receiver Array

A novel tracking method in the phased antenna array with a single-channel receiver for the moving signal source is presented in this paper. And the problems of the direction-of-arrival track and beamforming in the array system are converted to the power maximization of received signal in the free-interference conditions, which is different from the existing algorithms that maximize the signal to interference and noise ratio. The proposed tracking method reaches the global optimum rather than local by injecting the extra noise terms into the gradient estimation. The antenna beam can be steered to coincide with the direction of the moving source fast and accurately by perturbing the output of the phase shifters during motion, due to the high efficiency and easy implementation of the proposed beamforming algorithm based on the simultaneous perturbation stochastic approximation (SPSA). Computer simulations verify that the proposed tracking scheme is robust and effective