Drone localization using ultrasonic TDOA and RSS signal: Integration of the inverse method of a particle filter

Abstract

This paper will present an overview of indoor and outdoor drone localization methods. Outdoor scenarios almost always use a GPS with IMU. Indoor systems are using short-range sensors that are sensitive to the external conditions of the environment. Mostly used methods are optical flow and stereovision, while an ultrasonic transceiver system optimizes and provides high precision and orientation of the drone. An ultrasonic preceptor is integrated into a listener/beacon and can be used with referenced beacons inside a WSN. The Crossbow Cricket hardware platform, which is based on TDOA and RSS principle, is used for simulations and code development. The researched direction is the localization of referent nodes (beacons) concerning the listener which is mounted on a flying drone. For that purpose, a probabilistic approach is used, based on a Bayes filter, where the positions of the beacon can be observed like random variables. Considering that these distributions significantly vary from a Gauss distribution, it is appropriate to use a particle filter.

Drone SLAM using TDOA-RSS signal with applied EKF on PF data

“…With a simulation we isolate variables which can influence control parameters in real -time drone environment. The test case scenario was to use a testbed, where a listener on the drone receives signals from beacons based on TDOA-RSS (Time Differential of Arrival -Receiver Signal Strength) method [2,5]. In this way, we have calculated the distance between each node and a listener.…”

“…In Figure 8, we also have R t , which is the input parameter of insecurity, strictly for odometry while u t is insecurity of new measurement. Considered nonlinear system is described with difference equation and the observation model with additive noise (1) and (2) x = g x ,u…”

“…Localization and mapping using SLAM (Simultaneous Localization And Mapping) algorithm will be presented in indoor drone flight scenario. With corresponding drone hardware ARDrone 2.0, its created scenario which is based on TDOA-RSS (Time Differential Of Arrival -Receiver Signal Strength) inverse method of localization [1,2]. General idea is to use six ultrasonic beacons with listener.…”

“…General idea is to use six ultrasonic beacons with listener. This research and development platform (Crossbow Cricket) is modified for earlier scenario described in paper [2][3][4][5][6][7][8][9][10][11]. Simulations in Matlab are extended from 2D equations to 3D equation system.…”

“…In real-time behaviour scenario are used data from locally saved records. Controlling drone, integration of parser beacon data and algorithms integration are realized with LabView, National Instruments [2]. For writing/reading method is used FIFO (First -In -First -Out) Toolkit.…”