29-12-2014, 06:12 PM
Hello There. I would like to have a look at the MATLAB code for the Hybrid GPS GSM localization of automobile tracking using Kalman Filter.
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matlab code for hybrid gps gsm localization of automobile tracking system using kalman filter
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Hello There. I would like to have a look at the MATLAB code for the Hybrid GPS GSM localization of automobile tracking using Kalman Filter.
29-03-2017, 03:56 PM
An integrated GPS-GSM system is proposed to track vehicles using the Google Earth application. The remote module has a GPS mounted on the vehicle in motion to identify its current position and be transferred by GSM with other parameters acquired by the data port of the car as an SMS to a receiving station. The received GPS coordinates are filtered using a Kalman filter to improve the accuracy of the measured position. After data processing, the Google Earth application is used to view the location and current status of each vehicle. This objective of this system is to manage the fleet, the distribution of police cars and car theft precautions.
The Global Positioning System (GPS) has become one of the most advanced location systems that offers reliable estimates of mobile terminal (MT) location. However, there are situations where GPS is not available, for example, when the MT is used indoors or when the MT is located near tall buildings. In these scenarios, a promising approach is to combine GPS measured values with measured values of the Global System for Mobile Communication (GSM), which is known as a hybrid localization method. In this article, we propose a hybrid MT tracking algorithm based on a Rao-Blackwellized (RBUKF) non-aromatized Kalman filter that combines GPS pseudoranges with synchronization advancement and signal strengths received from GSM. The results of the simulation show that the proposed hybrid method exceeds the GSM method. In addition, the performance of the RBUKF is compared with the extended Kalman filter and the corresponding posterior Cramer-Rao boundaries.
The Global Positioning System (GPS) has become one of the most advanced location systems that offers reliable estimates of mobile terminal (MT) location. However, there are situations where GPS is not available, for example, when the MT is used indoors or when the MT is located near tall buildings. In these scenarios, a promising approach is to combine GPS measured values with measured values of the Global System for Mobile Communication (GSM), which is known as a hybrid localization method. In this article, we propose a hybrid MT tracking algorithm based on a Rao-Blackwellized (RBUKF) non-aromatized Kalman filter that combines GPS pseudoranges with synchronization advancement and signal strengths received from GSM. The results of the simulation show that the proposed hybrid method exceeds the GSM method. In addition, the performance of the RBUKF is compared with the extended Kalman filter and the corresponding posterior Cramer-Rao boundaries.
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