Two-Stage Channel Adaptive Algorithm for Unmanned Aerial Vehicles Localization with Cellular Networks

Abstract

Unmanned aerial vehicle (UAV) is regarded as a powerful tool to expand the existing ground wireless network into aerial space. Since high mobility is an essential characteristic for UAV, it is important to carry out an accurate, real-time, and high-precision localization in terms of safe operation and communication link maintenance. The cellular network-based localization technology has provided UAV a solution with both high coverage and seamless connection. However, the complex channel environment between the UAV and terrestrial base station (BS) would have weakened the localization performance. To solve this problem, a two-stage channel adaptive algorithm for cellular-connected UAV has been proposed. The first stage of the algorithm is to revise the observation error introduced by the complex channel environment using the model of DDPG. The second stage is to locate the UAV position with TDOA algorithm using the revised observation values. Simulation results have demonstrated that the proposed algorithm can achieve the channel adaptive effect by revising the observation errors and improve location performance greatly, especially for UAVs at a relative lower altitude.

Research on distributed radiation source collaborative localization technology based on unmanned aerial vehicle platform

“…indicates the distance between the target and the observation station, so the distance difference between the target and the main station and the target to other observation stations is [3][4][5][6][7][8][9][10][11][12][13][14][15][16] :…”

“…The above expressions have a total of i=1,2,..., M, which can be expressed in matrix form [3][4][5][6][7][8][9][10][11][12][13][14][15][16] :…”

“…The covariance matrix P of the positioning error is [3][4][5][6][7][8][9][10][11][12][13][14][15][16] :…”