Raytheon Tracker Technology for C4I
A prerequisite to the development of a COP is the ability to accurately track forces regardless of domain. Raytheon has developed a number of general purpose and specialized trackers that are the workhorses behind our leading C4I systems. During tracking, the system must associate multiple source plots with a track, and then smooth associated plots to estimate the target state in terms of position and velocity. The tracker must account for targets in close proximity, tracking in two and three dimensions, high-G maneuvers and clutter around a target. Different trackers can use different techniques to develop and maintain a track. Typical among these include statistical data association, dynamic clutter mapping and track branching (see Figure).
The tracking process typically starts with Automatic Track Initiation (ATI). ATI enables the operator to establish zones in which track initiation occurs without further operator action. The initiation criteria can include minimum and maximum target speed, altitude and the type of plots used for initiation (primary, secondary or both radar returns). The ATI function controls the false track initiation rate by automatically mapping ATI and remote track drop areas and, together with category selection, helps to alleviate operator workload. The system processes and integrates primary (radar) and/or secondary (beacon) plot messages representing the same target to initiate and maintain a single local track.
Raytheon trackers improve track continuity and accuracy using statistical data association methods for both active and passive (jamming) data, a variable update filtering schedule, Sequential Probability Ratio Testing (SPRT) for track initiation, and an Interacting Multiple Model (IMM) filter for track state estimation.
IMM uses multiple Kalman filters running in parallel to represent different potential maneuver states of the track. This enables the system to continue tracking highly evasive targets through high-G and high-speed maneuvers. When the plot-track association probability falls below the confidence level, track branching (two or more tracks that represent different hypotheses about the target's motion) revises the decision based on subsequently processed radar data. A probability is calculated for each branch, based on correlated plot data. A branch is deleted if its probability falls below an adapted threshold. The most probable branch is made available for display and other system functions.
Sensor registration computes and applies corrections to sensor data to compensate for atmospheric and other biases that affect the accuracy of that data in a systemic and repeatable way. Collimation computes corrections to range and azimuth needed to align a radar with its secondary (beacon) returns. Using a real-time, on-line algorithm, the system estimates and applies radar registration and collimation bias corrections. This reduces the effect of radar measurement bias errors, minimizes duplicate tracks and improves track accuracy. Together, SPRT track initiation, the multiple branch approach, the IMM filter, and automatic measurement bias estimation and removal provide superior tracking performance against small targets, maneuvering targets and targets in clutter.
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