Source-linked AI summary
Hybrid GPS-GSM Localization of Automobile Tracking System
Mohammad A. Al-Khedher
TL;DR
In-vehicle GPS signals can be inaccurate because of multipath and other measurement errors. This system sends vehicle coordinates and engine data by GSM SMS for Kalman-filter processing and Google Earth display; filtered coordinates are reported below 15 meters in 2DRMS accuracy, compared with about 43 meters for transmitted coordinates.
Problem
In-vehicle GPS positioning can be inaccurate because of multipath and other satellite, atmospheric, clock, and calculation errors.
Source: §6 · p. 6Method
Results
Filtered vehicle coordinates had 2DRMS accuracy below 15 meters, compared with about 43 meters for transmitted coordinates received by the in-vehicle GPS.
Source: §7 · p. 10Takeaways & Limitations
The system is presented for fleet monitoring and management, including monitoring vehicle status and location.
Source: §1 · p. 1, §2 · p. 2Further localization improvement could use map-matching techniques based on road information.
Source: §6 · p. 10
Abstract
from arXiv · showhide
An integrated GPS-GSM system is proposed to track vehicles using Google Earth application. The remote module has a GPS mounted on the moving vehicle to identify its current position, and to be transferred by GSM with other parameters acquired by the automobile's data port as an SMS to a recipient station. The received GPS coordinates are filtered using a Kalman filter to enhance the accuracy of measured position. After data processing, Google Earth application is used to view the current location and status of each vehicle. This goal of this system is to manage fleet, police automobiles distribution and car theft cautions.
1. Introduction
Automobile tracking systems aim to detect vehicle location and status. For large fleets, central management can reduce assignment costs and effort and support scheduling by vehicle location.
1. Introduction
- Accurately detecting a vehicle’s location and status is the main goal of automobile trajectory monitoring systems.Such systems use hybrid techniques combining wireless communication, geographical positioning, and embedded applications.Source: §1 · p. 1
- Central fleet management can reduce employee cost and effort on road assignments and enable scheduling based on current vehicle locations.The stated goal is to improve large enterprises’ productivity and meet varying customer requirements.Source: §1 · p. 1
2. Related work
Prior work and technologies motivate integrating GPS, GSM/SMS, embedded control, and Google Earth visualization to monitor vehicle location and status. The system is presented as relevant to fleet management and safety-related monitoring.
2. Related work
- Vehicle tracking research has used communication, GPS, GIS, remote control, and server systems, among other technologies.Source: §2 · p. 1
- GSM and SMS are described as widely available wireless data-transfer technologies, with SMS characterized as inexpensive, convenient, accessible, and reliable.Source: §2 · p. 2
- The proposed system integrates GPS and GSM modules with an embedded controller, and users can view vehicle locations graphically on Google Earth alongside fleet information.The system is intended to monitor automobiles’ status for particular users and purposes -; its components and visualization are described with references -.Source: §2 · pp. 1–2
- The system is presented as useful for monitoring parameters related to safety, emergency services, and engine stall.The paper describes its implementation as an application of modern technologies for fleet monitoring and management.Source: §2 · p. 2
3. System overview
The system uses a vehicle-mounted module to collect GPS and engine data and send them by SMS to a stationary receiving module. The receiver processes the data for Google Earth display, while system efficiency depends on communication-network sufficiency.
3. System overview
- The vehicle-mounted module reads GPS coordinates and selected engine parameters, processes them with a microcontroller, and sends the data to a server by GSM SMS.The selected parameters are RPM, engine coolant temperature, vehicle speed, and percent throttle.Source: §3 · p. 2
- The receiving GSM modem and workstation process SMS data, correct GPS readings with a Kalman filter, and convert an Excel file to KML for Google Earth display.The map displays automobile location and engine parameters.Source: §3 · pp. 2–3
- System efficiency depends on the sufficiency of the communication network.Source: §3 · p. 3
- An optional extension could connect the car alarm to alert the owner by cell phone, or connect the airbag system to report severe accidents and alert police and ambulance services with the location.Source: §3 · p. 3
4. Hardware specification
The vehicle unit receives GPS and OBD-II data and sends an SMS. Its specified hardware combines an MT3329 GPS receiver, microcontroller, and GSM module, with automobile-battery power and an emergency backup.
4. Hardware specification
- The tracking unit takes GPS output in NMEA 0183 format and data from the automobile’s OBD-II port, then sends an SMS using Hayes AT commands.Source: §4 · p. 3
- The selected engine-status parameters are RPM, engine coolant temperature, vehicle speed, and percent throttle; the SIM900D GSM module supports standard AT commands and several GSM networks.Transmission settings are 19200 bps, 8N1, with no flow control.Source: §4 · p. 3
- The MediaTek MT3329 GPS receiver supports up to a 10 Hz update rate and forwards latitude, longitude, and speed information to the microcontroller.Source: §4 · p. 4
- The tracking unit is designed to run from the automobile battery and includes an emergency backup power source.Source: §4 · p. 4
5. Software specification
The recipient station parses SMS data, corrects GPS positions, and converts the results for Google Earth. The displayed view combines automobile location with engine status, while Google Earth also supports live tracking.
5. Software specification
- The recipient uses the $GPRMC sentence for position and time to reduce SMS text, then receives coordinates and automobile status by GSM.The recipient processes the transmitted SMS, corrects the GPS reading with a Kalman filter, and exports the sorted results from Excel to KML for Google Earth.Source: §5 · p. 4
- Google Earth reads the KML file to show the automobile’s location and status, including OBD-II RPM, coolant temperature, vehicle speed, and throttle.The live view reports latitude and longitude alongside these engine parameters.Source: §5 · pp. 4–5, Figure 6 · p. 5
- Google Earth can track the automobile’s route from its beginning, with data saved in separate Excel sheets.Figure 7 shows live tracking of the targeted automobile.Source: §5 · p. 5, Figure 7 · p. 6
6. Error correction of in-vehicle GPS coordinates using Kalman filtering
The section describes GPS error sources, a Kalman-filter correction procedure, and its accuracy evaluation. Corrected positions had substantially lower reported 2DRMS error than in-vehicle GPS readings, with mapped pins within the road width.
6. Error correction of in-vehicle GPS coordinates using Kalman filtering
- Near-ground reflections from buildings cause multipath, while satellite geometry, orbit shifts, clock errors, atmospheric effects, and calculation errors also affect GPS accuracy.Prior approaches included four vehicle-mounted GPS antennas or differential correction using fixed earth stations; the former increases cost and computational complexity.Source: §6 · p. 6
- The system applies a Kalman filter to reduce GPS errors, with the stated goal of matching Differential GPS precision.The in-vehicle unit sends coordinates by GSM to a reference station, where the data is evaluated to estimate automobile-location errors.Source: §6 · p. 6
- For GPS correction, the Kalman filter state comprises receiver coordinates (Gx, Gy, Gz) and clock-offset error bu; its transition matrix is identity 4×4, with zero-mean white Gaussian process noise (covariance Qk) and Gaussian measurement noise (covariance Rk).Source: §6 · p. 7
- GPS measurements use satellite pseudoranges based on satellite-to-receiver range plus receiver clock offset; the measurement vector includes readings from at least four satellites.The range is linearized about estimated receiver coordinates.Source: §6 · pp. 6–7, Figure 8 · p. 7
- 2DRMS summarizes estimated-coordinate latitude and longitude deviations and represents typical 95–98% probability values when those deviations may differ.The paper calculates 2DRMS from the latitude and longitude standard deviations.Source: §6 · p. 8
- 13.7 meter corrected versus 42.8 meter in-vehicle GPS 2DRMS accuracy across 2,000 measurements; corrected pins fell within the road width (<14 meter).Figure 10 reports latitude and longitude standard deviations of 5.3 and 4.3 meters after filtering, versus 13.6 and 16.5 meters for the in-vehicle receiver.Source: §6 · pp. 8–9, Figure 10 · p. 9
- Road-information map matching is proposed as a further way to improve automobile localization accuracy.The section’s map comparison shows corrected tracking paths alongside transmitted GPS positions.Source: §6 · pp. 9–10, Figure 11 · p. 9
7. Conclusion
The conclusion presents a real-time automobile tracking system that sends location and status by SMS and displays processed information in Google Earth. Kalman filtering improves reported coordinate accuracy from about 43 meters to less than 15 meters.
7. Conclusion
- The system combines an in-vehicle GPS-GSM transmitting module with a stationary receiver that processes data into a Google Earth-compatible format for online remote monitoring.The transmitted SMS carries automobile location and status information.Source: §7 · p. 10
- Kalman filtering is applied to transmitted vehicle locations to improve tracking accuracy.The receiving module collects and processes the transmitted information for Google Earth display.Source: §7 · p. 10
- Filtered coordinates had less than 15 meters 2DRMS accuracy, compared with about 43 meters for coordinates from the in-vehicle GPS module.The conclusion describes this as an enhancement in estimated vehicle-coordinate accuracy.Source: §7 · p. 10