i am going to find the challenges and new fields opened up in the target tracking for research in academy. please mention some references in addition to titles to make the subject self contained.
Hello. Target tracking is getting to be quite a big field in the sense of more widely applicable. Check out the Information Fusion conferences. In my opinion, the main challenge is in development of analysis tools (NOT Monte Carlo) for tracking algorithms so engineers can actually design them. This is a very hard area and there hasn't been a lot of progress on it. Algorithms for MTT are plentiful, but comparisons on common data sets are not. So another area is benchmarking of tracking algorithms on common simulated and real data. The major developments in the last 10 or so years are particle filters (a simulation based approach) and set-based methods (e.g. the PHD filter).
You can have a look at a survey paper I wrote on MTT a few years ago that came out just as these newer techniques were coming out.
With a colleague, I recently added a challenging sonar 1-D data set you might like to look at also.
Article Taxonomy of multiple target tracking methods
Technical Report Benchmark 4-target passive sonar scenario description for 1-D tracking
Hi,
Graham resumes well the situations. Much progress has also been made to handle specific target tracking (e.g. unresolved targets, extented targets, hard-cluttered environments). The "PHD-filtering" community shows also a rising interest to multiple-model problems.
An alternative research interest concerns for example the research of exact solution, the so called labeled random finite sets. This is a promising way to handle different tracking problems.
One of the main task is indeed to evaluate several tracking approaches to establish a well-known benchmark (as done by Nguyen in the detection field), which is not so easy due to specificities of each related method.
Article Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter
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