ES-DPR: A DOA-Based Method for Passive Localization in Indoor Environments

Abstract

In this paper, we propose a novel indoor passive localization approach called eigenspace-based DOA with direct-path recognition (ES-DPR), based on a DOA estimation algorithm with multiple omnidirectional antennas deployed in a uniform linear array (ULA). To address the multipath propagation interference problem in the indoor environments, we utilize the azimuth and RSS estimation results, which are calculated by using the eigenspace-based DOA (ES-DOA) algorithm, in a novel style. A direct-path bearing recognition algorithm is introduced to identify the real DOA of the signal source in different indoor environments, by combining the azimuth and RSS estimation with ensemble learning methods. Numerical simulations are conducted to verify the validity and superiority of the proposed method. The results show that the proposed ES-DPR method can achieve high resolution and has strong anti-noise capability in dealing with the multipath signals, and the direct-path recognition algorithm is reliable and robust in different indoor environments, even in undetectable direct-path conditions.

FFK: Fourier-Transform Fuzzy-c-means Kalman-Filter Based RSSI Filtering Mechanism for Indoor Positioning

“…Time of Arrival and Time Difference of Arrival are ideal approaches for 3D indoor positioning based on their design advantages [8]. Direction of Arrival utilizes the azimuth to establish an eigenspace for removing multipath propagation interferences [10]. These approaches usually require customized sensor configurations or deployments to fulfill their deployment requirements.…”

“…Time of Arrival can integrate with Kalman filter and Gaussian mixture models to remove Non-Line of Sight (NLOS) signals for accurate indoor positioning [7], and this can be used for 3D indoor positioning [8]. Time Difference of Arrival [9] and Direction of Arrival [10] can provide enhanced positioning techniques, and they usually require customized sensor configurations or deployments to fulfill their design requirements.…”

Sensors and Sensing Technologies for Indoor Positioning and Indoor Navigation

“…Indoor passive localization is also the focus of the approach described in [ 15 ], called eigenspace-based DOA with direct-path recognition (ES-DPR). It is based on a Direction of Arrival (DOA) estimation algorithm with multiple omnidirectional antennas deployed in a uniform linear array (ULA).…”

Tracking by Risky Particle Filtering over Sensor Networks

“…The problem can be classified by three main methods that can be employed for the tracking application according to the type of physical measurement read at sensors. The main types of measurements are the time delay of arrival (TDOA) [7,8], the direction of arrival (DOA) [9,10], and the received signal strength (RSS) [11][12][13][14][15][16][17][18][19] of the signal generated from the tracked target, respectively. RSS measurement of the sensors represents received energy or power emitted by the target.…”