Hyowon Kim

Kalman-based mobility tracking with range-free localization under a realistic device distribution

The performance of range-free localization is vulnerable to change of connectivity information. To solve the problem, we propose a Kalman-based mobility tracking algorithm combined with range-free localization under a realistic device distribution. We considered a large indoor environment of a real shopping mall for the performance evaluation. To simulate the real propagation scenario, the radio irregularity was applied on the map of the shopping mall according to the location of devices. We demonstrate that the Kalman-based mobility tracking with range-free measurements outperforms the range-free only localization algorithm. Various factors such as the device distribution density, radio irregularity, and communication range influencing the tracking performance was analyzed.

Measurement fusion of connectivity and received signal strength for indoor localization and tracking

The range-free localization suffers from unstable connectivity information between wireless devices. To overcome this, we propose a Markov Chain Monte Carlo particle filter (MCMC PF)-based mobility tracking algorithm assisted by received signal strength (RSS) information. The range-free localization results and RSS measurements are used in the tracking algorithm. From MATLAB simulation, we confirm the performance of the proposed tracking algorithm compensating the defect of the range-free localization, and the efficient indoor mobility tracking in a realistic indoor environment has been demonstrated.

Performance analysis of cooperative quickest interference detection for GNSS

In this paper, we present a performance of cooperative quickest interference detection for GNSS. Various schemes for interference detection have already been studied in GNSS literature, the purpose is to focus on a reliable and fast detection. We consider cooperative detection using the CUSUM test in multi-GNSS receiver scenario. The proposed approach results of simulation show the fundamental framework to apply GNSS of cooperative quickest detection.

Performance analysis of DOA estimation in the presence of mutual coupling for UAV

In this paper, we analyze performances of direction of arrival (DOA) estimation with existence of mutual coupling. Received signals are in different degrees, and equal power uncorrelated. The method in this paper proceeds in three steps. We consider a steering vector which is applicable to unmanned aerial vehicle (UAV). Then we analyze differences between theoretical DOA estimation and practical DOA estimation with mutual coupling. We propose an improved approach of estimation with mutual coupling. Simulation results demonstrate effectiveness and accuracy of the improved approach under various conditions.

A hyperbolic distance measurement model for range-free localization in anisotropic networks

This paper presents a hyperbolic distance measurement model where the difference between the distances from a normal node to two anchors is defined as the sum of the difference between the distances from another anchor to the anchors and an error. A hyperbolic range-free localization algorithm is then introduced based on the proposed model for anisotropic networks. The proposed algorithm estimates the location of each normal node by selecting hyperbolic distance measurements with maximum errors less than a predefined threshold. Simulation results show the superiority of the proposed algorithm over existing range-free localization algorithms.