What are the two types of tracking measures?
- Measures of performance (MOP)
- measures of effectiveness (MOE)
What are the two broad categories for MOP and MOE?
- Sensor-related
- sensor characteristics
- Tracker-related
- algorithm-free and algorithm-dependent
Give some information on Algorithm and Algorithm Free
- Algorithm Dependent
- Track scores in the Multiple Hypothesis tracker
- Algorithm Free
- Applicable to any tracker
What are different types of Tracker
- Single-hypothesis tracker
- Multiple-hypothesis tracker
- Probabilistic data association tracker
What is a great way to track maneuvering targets better?
- Estimate the motion of the targets by using various models
What are some objectives of target tracking? What are some of the concerns that tracking wants to answer?
“
- How many objects are there?
- Where are the objects located in space?
- What is their speed and direction of motion?
- How do the objects maneuver relative to each other?
“
What is one challenge in detecting/tracking closely separated targets?
- If the targets are in one sensor resolution cell, then only one target will be reported
What is the simplest choice for multi-target tracking?
- Single-hypothesis tracker like the GNN
How does interacting multiple-model (IMM) help in tracking?
- IMM can help to find the correct motion models of the targets
What can help with broken tracks?
- a multiple-hypothesis tracker (MHT)
How does MHT help with this?
- It can create and maintain multiple tracks for ambiguous situations and
- then resolves for ambiguity for better tracking
- MHT can improve the tracking when the targets turn (and go away from one another)
Compare JPDA and MHT
- MHT can be slower than JPDA
- JPDA can be thought of sub-optimal tracking where MHT is more optimal tracking
- MHT is usually slower
How does JPDA work and how is this different from MHT?
- “JPDA allows a single detection to be used for updating multiple tracks in its vicinity. Moreover, multiple detections can be clustered together with several tracks and update each of those tracks. This resolves the issue of the broken track.”
How is track status kept in JPDA for ambiguous regions?
- Confirmed
Can IMM be used with JPDA?
- Yes
How does IMM with JPDA help?
- Provides better before turn tracking
- the turn before the ambiguity region is better addressed
Are GNN and JPDA faster than MHT?
- Yes
Give an example when the Constant Velocity model does not give better tracking?
- Maneuvering targets
- How can that be improved
- Use IMM
The algorithms as discussed which one is the best overall and in general
- JPDA
Still JPDA is faster and great, can there be a scenario where JPDA is not appropriate?
- Too much ambiguity where JPDA or GNN cannot give proper tracking
References: The fusion example TrackingCloselySpacedTargetsUnderAmbiguityExample in Matlab document
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