Abstract
For radar systems with low update rates; such as track-while-scan (TWS) systems using rotating phased array antennas; reducing the prediction error is a very important issue. A good interacting multiple models (IMM) hybrid filter combined with circular and linear filters that are defined in relation to three measurements has been proposed in the literature. However; the algorithm requires three previous measurements; and too much prior information will result in a reduced ability to predict the future position of a highly maneuvering target. A new circular prediction algorithm for maneuvering target tracking is proposed as a non-linear prediction filter in this paper. Based on this new predictor; we also proposed a new type of IMM filter that has good estimation performance for high maneuvering targets. The proposed hybrid filter is entirely defined in relation to two measurements in a three-dimensional space to obtain a better maneuver following capability than the three measurements hybrid filter. Two target profiles are included for a comparison of the performance of our proposed scheme with that of the conventional circular; linear and IMM filters. The simulation results show that under low update rates; the proposed filter has a faster and more stable estimation response than other filters
Highlights
Radar tracking capability is an important factor in the performance of weapon systems
Small size rotary phased array radars are widely used due to their light weight, low price, and high mobility. They must use a track-while-scan (TWS) method to track the target under low update rate conditions
For this reason, implementing an appropriate mathematical model for optimal tracking performance is an important issue for low update radar systems
Summary
Radar tracking capability is an important factor in the performance of weapon systems. The state estimate of the tracking filter must be correctly compensated according to the lateral acceleration value [1] These steps illustrate that a good target tracking performance must be based on an exact mathematical model and a fast update rate. A good mathematical model is key in determining target tracking performance, especially for low update rate radar systems. The main problem of the coordinated turn model is that it is a set of non-linear coupled equations and, difficult to solve Another geometry-based circular prediction method, known as center point approach (CAP), has been introduced to address tracking problems. This paper focuses on the development of a three-dimensional tracking algorithm that constrains the predicted state to a circular and linear path for a low update rate radar system.
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