GPS-free Geolocation using LoRa in Low-Power WANs. Bernat Carbonés Fargas, Martin Nordal Petersen 08/06/2017

Transcription

1 GPS-free Geolocation using LoRa in Low-Power WANs Bernat Carbonés Fargas, Martin Nordal Petersen 08/06/2017

2 Outline 1. Introduction 2. LoRaWAN for geolocation 3. System design 4. Multilateration in LoRaWAN networks 5. Tests and results 6. Conclusions 2 DTU Fotonik, Danmarks Tekniske Universitet

3 1. Introduction Elderly assisted living à Global Navigation Satellite System (GNSS) available Main problem à Battery lifetime Goal à Design and implement a tracking IoT system in a LPWAN capable of transmitting the current position using low power technologies 3 DTU Fotonik, Danmarks Tekniske Universitet

4 Outline 1. Introduction 2. LoRaWAN for geolocation 3. System design 4. Multilateration in LoRaWAN networks 5. Tests and results 6. Conclusions 4 DTU Fotonik, Danmarks Tekniske Universitet

5 2. LoRaWAN for geolocation (I) Features Long range -> 5 km urban / 15 km rural Low power consumption Low data rate -> From 250 bps to 50 kbps Bandwidth bigger than other IoT technologies in LPWANs Previous studies presented good results Open source 5 DTU Fotonik, Danmarks Tekniske Universitet

6 2. LoRaWAN for geolocation (II) LoRa Physical layer Chirp Spread Spectrum (CSS) Forward Error Correction (FEC) LoRaWAN MAC protocol Bidirectional Standardized Source: LoRaWAN Specification - LoRa Alliance 6 DTU Fotonik, Danmarks Tekniske Universitet

7 Outline 1. Introduction 2. LoRaWAN for geolocation 3. System design 3.1 System structure 3.2 End-node 3.3 Gateways 3.4 Server 3.5 Application 4. Multilateration in LoRaWAN networks 5. Tests and results 6. Conclusions 7 DTU Fotonik, Danmarks Tekniske Universitet

8 3.1 System structure LoRaWAN ID/UDP MQTT Important information à Time each packet was received by each gateway to apply multilateration 8 DTU Fotonik, Danmarks Tekniske Universitet

9 3.2 End-node End-node Gateways Server Application Transmit GPS data through LoRaWAN module Elements Waspmote LoRaWAN module GPS receiver 9 DTU Fotonik, Danmarks Tekniske Universitet

10 3.3 Gateways End-node Gateways Server Application Time received packet Forward data to server via UDP/IP 4 Kerlink gateways à Embedded GPS 10 DTU Fotonik, Danmarks Tekniske Universitet

11 3.4 Server End-node Gateways Server Application Decode data from the gateways and transmit it to the application The Things Network (TTN) Open Source Third-party apps 11 DTU Fotonik, Danmarks Tekniske Universitet

12 3.5 Application End-node Gateways Server Application Parse and insert the information to a database Elements Java Application + MQTT client MySQL 12 DTU Fotonik, Danmarks Tekniske Universitet

13 Outline 1. Introduction 2. LoRaWAN for geolocation 3. System design 4. Multilateration in LoRaWAN networks 4.1 Geolocation techniques 4.2 Algorithm structure 4.3 Extraction of TDOAs 4.4 Detection of outliers 4.5 Non-iterative algorithm 4.6 Iterative algorithm 5. Tests and results 6. Conclusions 13 DTU Fotonik, Danmarks Tekniske Universitet

14 4.1 Geolocation techniques (I) Triangulation Angles of incidence Triangle defined with angles Trilateration Distance between transmitter and receiver à Time Of Flight (TOF) à Requires Synchronization Intersection of three circles 14 DTU Fotonik, Danmarks Tekniske Universitet

15 4.1 Geolocation techniques (II) Multilateration No synchronization à Time Difference Of Arrival (TDOA) Intersection of at least two hyperbolas (3 antennas required) 15 DTU Fotonik, Danmarks Tekniske Universitet

16 4.2 Algorithm structure 16 DTU Fotonik, Danmarks Tekniske Universitet

17 4.3 Extraction of TDOAs Extraction TDOA Detection of outliers Non-iterative algorithm Iterative algorithm Compute TDOA based on a pair of UTC times per each packet t "# = t " t # i, j = 1: 4 j i Where t " = time packet was received by gateway i 17 DTU Fotonik, Danmarks Tekniske Universitet

18 4.4 Detection of outliers Extraction TDOA Detection of outliers Non-iterative algorithm Iterative algorithm Definition (Barnett and Lewis): An observation which appears to be inconsistent with the remainder of that set of data Methods to detect outliers Grubb s test Tietjen-Moore test Generalized Extreme Studentized Deviate (ESD) test 18 DTU Fotonik, Danmarks Tekniske Universitet

19 4.5 Non-iterative algorithm (I) Extraction TDOA Detection of outliers Non-iterative algorithm Based on a linear multilateration 4 gateways à TDOAs Location of the 4 gateways Coordinates conversion required Geodetic (latitude, longitude) ßà Cartesian (x, y) Reference ellipsoid WGS-84 (GPS) Iterative algorithm 19 DTU Fotonik, Danmarks Tekniske Universitet

20 4.5 Non-iterative algorithm (II) Extraction TDOA Detection of outliers Non-iterative algorithm Iterative algorithm 20 DTU Fotonik, Danmarks Tekniske Universitet

21 4.6 Iterative algorithm (I) Extraction TDOA Detection of outliers Non-iterative algorithm Iterative algorithm Avoid coordinates transformation à Error propagation Solution à Iterative algorithm Haversine formula à Compute the distance between two points over the globe 21 DTU Fotonik, Danmarks Tekniske Universitet

22 4.6 Iterative algorithm (II) Extraction TDOA Detection of outliers Non-iterative algorithm Iterative algorithm Create two grids of possible latitude and longitude values Find the minimum error 22 DTU Fotonik, Danmarks Tekniske Universitet

23 Outline 1. Introduction 2. LoRaWAN for geolocation 3. System design 4. Multilateration in LoRaWAN networks 5. Tests and results 5.1 Test spots 5.2 Non-iterative algorithm 5.3 Iterative algorithm 6. Conclusions 23 DTU Fotonik, Danmarks Tekniske Universitet

24 5.1 Test spots C à 168 samples B à 1728 samples 24 DTU Fotonik, Danmarks Tekniske Universitet A à 454 samples

25 5.2 Non-iterative algorithm Mean Absolute Localization Error (MALE) Mean estimator à F t AB = 1 N D t ABE EGH 25 DTU Fotonik, Danmarks Tekniske Universitet

26 5.3 Iterative algorithm (I) 26 DTU Fotonik, Danmarks Tekniske Universitet

27 5.3 Iterative algorithm (II) 27 DTU Fotonik, Danmarks Tekniske Universitet

28 Outline 1. Introduction 2. LoRaWAN for geolocation 3. System design 4. Multilateration in LoRaWAN networks 5. Tests and results 6. Conclusions 6.1 Future work 28 DTU Fotonik, Danmarks Tekniske Universitet

29 6. Conclusions IoT tracking system using LoRa LoRaWAN presents attractive features Long range Low power consumption Two designed algorithms à Accuracy 100 meters Real-time tracking application à Not usable Mean estimator improves accuracy 29 DTU Fotonik, Danmarks Tekniske Universitet

30 6.1 Future work Kerlink gateways Clock Increase amount Multipath To resolve à Bandwidth signal Algorithm Machine Learning to combine TDOAs with RSSI measurements K-Nearest Neighbors to improve the accuracy in real-time 30 DTU Fotonik, Danmarks Tekniske Universitet

31 31 DTU Fotonik, Danmarks Tekniske Universitet