87th AMS Annual Meeting

Thursday, 18 January 2007: 8:30 AM
Target tracking at the National Weather Radar Testbed: a progress report on detecting and tracking aircraft
217A (Henry B. Gonzalez Convention Center)
Mark Yeary, University of Oklahoma, Norman, OK; and B. McGuire, D. Forsyth, W. Benner, G. Torok, and M. B. Yeary
Poster PDF (315.0 kB)
This paper describes point target detection with the new Phased Array Radar (PAR) at the National Weather Radar Testbed (NWRT) in Norman, Oklahoma. Differing from conventional radars, such as the WSR-88D, the NWRT is designed to be multi-function. That is, it can detect both volumetric and point targets (such as aircraft). This paper will be geared towards point target detections and how these can be incorporated into a tracker. To begin, the paper discusses the radar's waveform design differences that are used to distinguish between volumetric targets and point targets. This also includes clutter mitigation, dwell time assignments, and radar scheduling issues with the radar's control system.

Once the detections have been made, these observations can be input to a tracking algorithm. This will be the focus of the second part of the paper. As commonly accepted, typical or friendly targets are “non-maneuvering.” By definition, they do not possess strong accelerations along their respective velocity vectors. However, uncooperative or unfriendly targets may experience erratic behavior on an undocumented flight plan. This behavior is modeled by significant accelerations or maneuvers. At the current time, developing tracking algorithms for these targets is of homeland interest. The dynamic properties of these maneuvers are highly non-linear. As discussed in the most recent literature, particle filtering is defined as an emerging Monte-Carlo non-linear state estimation method. As typically done, the Kalman filter is employed for the tracking of targets (either point target or distributed), and particle filters will offer greater accuracy in their tracking. Particle filters are excellent for non-linear tracking problems. The non-linear tracking problem is described when the path of the moving or dynamic target is modeled by non-linear differential equations. The particles are sampling points of the probability distribution of the system. By doing this, the particle filter can circumvent the usual problems associated with Kalman filter. In the results section of the paper, the team's aircraft detection results using the National Weather Radar Testbed will be depicted with their respective tracks.

On a national basis, airport capacity has increased by only 1 percent in the past 10 years, while air traffic increased 37 percent during that time, as reported by the American Society of Civil Engineers. It is clear that America's infrastructure is aging. Providing discipline specific solutions will be extremely costly. However, by working together, a diverse group of scientists and engineers can develop the individual radars can be used in a multi-function capacity to provide both weather and target tracking data. This strategic alliance greatly reduces costs, while providing enormous benefits to the public.

The full conference paper will discuss our progress of this project: current laboratory findings, successes, and future risk mitigation strategies for subsequent designs. Future work will also be discussed.

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