Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets

1970/07/01 by Robert Singer, Robert A. Singer · 15 citations
Computer Science · Engineering · #Target Tracking and Data Fusion in Sensor Networks #Inertial Sensor and Navigation #Guidance and Control Systems

paper · doi:10.1109/taes.1970.310128

Abstract

The majority of tactical weapons systems require that manned maneuverable vehicles, such as aircraft, ships, and submarines, be tracked accurately. An optimal Kalman filter has been derived for this purpose using a target model that is simple to implement and that represents closely the motions of maneuvering targets. Using this filter, parametric tracking accuracy data have been generated as a function of target maneuver characteristics, sensor observation noise, and data rate and that permits rapid a priori estimates of tracking performance to be made when maneuvering targets are to be tracked by sensors providing any combination of range, bearing, and elevation measurements.

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Related

• Survey of maneuvering target tracking. part v: multiple-model methods
• Tracking an Object with Unknown Accelerations using a Shadowing Filter
• Analysis of performance criteria for optimization based bearing only target tracking algorithms
• Kalman filter versus IMM estimator: when do we need the latter?
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