Experimental Performance Evaluation of Outdoor TDoA and RSS Positioning in a Public LoRa Network

Abstract

This paper experimentally compares the positioning accuracy of TDoA-based and RSS-based localization in a public outdoor LoRa network in the Netherlands. The performance of different Received Signal Strength (RSS)-based approaches (proximity, centroid, map matching,...) is compared with Time-Difference-of-Arrival (TDoA) performance. The number of RSS and TDoA location updates and the positioning accuracy per spreading factor (SF) is assessed, allowing to select the optimal SF choice for the network. A road mapping filter is applied to the raw location estimates for the best algorithms and SFs. RSS-based approaches have median and maximal errors that are limited to 1000 m and 2000 m respectively, using a road mapping filter. Using the same filter, TDoA-based approaches deliver median and maximal errors in the order of 150 m and 350 m respectively. However, the number of location updates per time unit using SF7 is around 10 times higher for RSS algorithms than for the TDoA algorithm.

A Reproducible Comparison of RSSI Fingerprinting Localization Methods Using LoRaWAN

“…Plets et al [3], have evaluated experimentally RRS and TDoA ranging positioning methods using a LoRaWAN network, reporting median errors of 1250 and 200 meters for RRS and TDoA respectively. Other works [4], [5], have focused on rather specific settings over which they evaluate positioning methods.…”

LoRaWAN Geo-Tracking Using Map Matching and Compass Sensor Fusion

“…The most accessible and available way to localize sensor nodes in a LoRaWAN network is by using the RSS metadata that is received by the gateways after an uplink. Such approaches have been studied in our previous works in [ 15 , 16 ]. In [ 15 ], the RSS received from up to three gateways was converted to a location using different algorithms, yielding a median accuracy between 1250 m and 2500 m. In case of frequent uplinks and when the mode of transportation is known, map matching further reduced the median error to 700 m. In [ 16 ], a mean accuracy around 400 m was obtained with an RSS fingerprinting method based on the collection of a large training database.…”

“…Based on the observed time stamps and the known gateway locations, a Time-Difference-of-Arrival (TDoA) algorithm can estimate the location more accurately than RSS-based methods. Previous research [ 13 , 15 , 18 ] reported a median accuracy around 200 m when using this method in combination with a maximum likelihood (ML) algorithm. Similar accuracies of around 100 m were reported in [ 19 ] for the case of a privately deployed network with static nodes.…”

Investigation of the Performance of TDoA-Based Localization Over LoRaWAN in Theory and Practice

“…A very similar approach to ours is taken in [ 13 ], where the results around 100 m are achieved, but only on stationary positioned end-devices. Satisfactory results are provided by [ 14 ] using TDoA achieving 200 m error and RSS error estimation around 1.2–2.5 km, unfortunately without further details of implementation. In the paper [ 15 ] authors reported the median estimation error more than 400 m for stationary device using (V1) GWs.…”