Abstract
Normally in tracking applications, the target motion is usually modeled in Cartesian coordinates but, most sensors measure target parameters in polar coordinates. In this paper two contributions are considered in target tracking. One depends on position measurements and another one is on Doppler measurements. The position measurements are measured by taking the range and bearing (angle) of the target depending on the sensor location. Tracking the target Cartesian coordinates by using this range and bearing measurements is a nonlinear state estimation problem. To calculate the position measurements (range and angle), it is preferred to convert them to Cartesian coordinates by considering the linear form values. This is done, to avoid using nonlinear filters. This method is called as converted position measurement Kalman filter (CPMKF). In this paper another contribution is Doppler (range rate) measurement in target tracking systems. In this contribution the nonlinear pseudo states are calculated. This method is called as Converted Doppler measurement Kalman filter (CDMKF). By considering these two methods a parallel filtering structure, called statically fused converted measurement Kalman filter (SF-CMKF) is proposed. The two methods are operated along with each other to construct the new state estimator SF-CMKF by a static estimator to obtain final state estimates.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.