%0 Journal Article %1 noauthororeditor %A Sharma, Rahul %D 2014 %E Kumar, Dr. Shiv %J International Journal of Innovative Science and Modern Engineering (IJISME) %K %N 12 %P 3-6 %T Vehicle Tracking in Extreme Noisy Channel through Kalman Filter %U https://www.ijisme.org/wp-content/uploads/papers/v2i12/L07421121214.pdf %V 2 %X Kalman Filter is one of the most important discoveries for a signal processing engineer. It uses a system's dynamics model (i.e., physical laws of motion), known control inputs to that system, and measurements (such as from sensors) to form an estimate of the system's varying quantities (its state) that is better than the estimate obtained by using any one measurement alone. This paper tries to estimate the correct position of a vehicle in an extreme noisy channel and compares it to the conventional filtering methods like running average etc. The paper presents threshold based technique along with Gaussian filtering to differentiate object from the background and estimates the two dimensional position of the vehicle.

@article{noauthororeditor, abstract = {Kalman Filter is one of the most important discoveries for a signal processing engineer. It uses a system's dynamics model (i.e., physical laws of motion), known control inputs to that system, and measurements (such as from sensors) to form an estimate of the system's varying quantities (its state) that is better than the estimate obtained by using any one measurement alone. This paper tries to estimate the correct position of a vehicle in an extreme noisy channel and compares it to the conventional filtering methods like running average etc. The paper presents threshold based technique along with Gaussian filtering to differentiate object from the background and estimates the two dimensional position of the vehicle.}, added-at = {2021-09-22T10:36:57.000+0200}, author = {Sharma, Rahul}, biburl = {https://www.bibsonomy.org/bibtex/2e07fa36bc9e079c2434c12407bb5efb1/ijisme_beiesp}, editor = {Kumar, Dr. Shiv}, interhash = {017d71c792879a5caa4cf4d1c472a163}, intrahash = {e07fa36bc9e079c2434c12407bb5efb1}, issn = {2319-6386}, journal = {International Journal of Innovative Science and Modern Engineering (IJISME)}, keywords = {}, language = {En}, month = {November}, number = 12, pages = {3-6}, timestamp = {2021-09-22T10:36:57.000+0200}, title = {Vehicle Tracking in Extreme Noisy Channel through Kalman Filter}, url = {https://www.ijisme.org/wp-content/uploads/papers/v2i12/L07421121214.pdf}, volume = 2, year = 2014 }