Massachusetts Institute of Technology

Qualcomm Incorporated

Yuan Shen

Moe Z Win

Tao Luo

Juan Montojo

Wenhan Dai

Santiago Mazuelas

A method for localizing one or more devices in an environment make use of repeated allocation of resources for one or more sensor measurements. Each sensor measurement is characterized by the amount of resources allocated to the measurement, by a quality factor, and by direction-dependent characteristics of information that is obtainable from that sensor measurement. Knowledge of a current location of each of the one or more devices determined from past sensor measurements is characterized by a distribution, with each of the distribution containing information about the current location of the device, including the direction-dependent information and the uncertainty of the location. The allocation of resources makes use of the quality factors and direction-dependent characteristics of the sensor measurements, in combination with the distributions characterizing the current location of each of the one or more devices to allocate a variable amount of a resource to each of the one or more sensor measurements.

Variable resource allocation for localization

A general framework for parametric filters is based on belief condensation (BC), which can cope with highly nonlinear and non-Gaussian system models. The methodology exploits the specific structure of the problem and decomposes it in such a way that the linear and Gaussian part can be solved in closed form, while the remaining parts are addressed by an optimization process, referred to as BC. Simulation results show that the performance of the proposed BC filter is close to that of the particle filter, but with a much lower complexity.

Tracking a body by nonlinear and non-Gaussian parametric filtering

Systems and methodologies are described that effectuate or facilitate detecting a cell (serving or neighboring cell) in multichannel wireless communication environments. In accordance with various aspects set forth herein, systems and/or methods are provided that receive signals from multiple cells and identify candidate cells based at least in part on the received signals, compare signal metrics for each of the candidate cells, select signal metrics associated with each of the candidate cells, and compare signal metrics to identify proximate base stations located within a candidate cell.

Growing community of inventors

Cambridge, MA, United States of America

Yuan Shen