Multiple object tracking using radar data and extended kalman filter

Question

thanks in advance. I am new to the multiple object tracking field. So, I have been working on this for a couple of days. I have developed my first version of a single object tracker using an extended Kalman filter. I am estimating position, velocity by assuming a constant acceleration model. Now my question is how can I convert the existing model for multiple objects tracking. The main problem is I am using radar data. So, I am not able to get the references for developing the tracker. So, One good example or steps to achieve can help me in understanding the concept.

Answer 1

The answer to this question depends on a lot of things. For example, how much control and knowledge do you have over the whole system? If you know how many targets you need to track you can add all of them to the Kalman Filter state and for every measurement you perform data association to find out to which object a given measurement belongs. An easy association metric would be nearest neighbor.

If you don't know how many targets there will be you will want to implement a track management where each target you are tracking represents a track and you can model birth and death probabilities of targets.

Multi Target Tracking is a vast field and if you want to have an in-depth mathematical introduction I would recommend the 2015 survey paper " Multitarget Tracking " by Ba-Ngu Vo et al . You should be able to find a preprint pdf online.

If you are looking more for a lightweight tutorial I would assume it should be possible to find some tutorial or example code online where to start. As mentioned in the first paragraph, nearest neighbor association for a fixed amount of objects might be a good first step.