A Damped Oscillation Model for Tracking Near Space Hypersonic Gliding Targets

Li, Fan; Jia-jun, Xiong; Qu, Zhiguo; Lan, Xuhui

doi:10.1109/taes.2019.2897517

Cited by 19 publications

(11 citation statements)

References 18 publications

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“…On the basis of this assumption, the acceleration autocorrelation of the DO model may be described as the damped oscillation function as Eq. ( 1) [4]. And for clarity and convenience of brevity some key notations and instructions are listed in…”

Section: Introductionmentioning

confidence: 99%

Near Space Hypersonic Vehicle Target Tracking Adaptive Non-Zero Mean Model

Fan¹,

Jia-jun²,

Chen³

et al. 2022

IEEE Access

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As a typical maneuver model, the second-order Markov model, which is based on acceleration periodic autocorrelation, is an effective way used for tracking near space hypersonic vehicle(NSHV) target tracking. It is found that, however, the model responds slowly to the target maneuvering and has weak maneuverability. To solve this problem, the adaptive non-zero mean damped oscillation model (ANM-DO), which based on the idea of mean compensation, is proposed. Then the difference of the mean compensation method between the first order Markov model and the two order Markov model is analyzed, and the physical essence of adaptive nonzero mean is discussed from time domain and frequency domain. Furthermore, to further investigate the performance of the ANM-DO model, we deduced the systematic dynamic errors of ANM-DO taking Kalman Filter (KF) as filtering algorithm. On this basis, the superior performance of ANM-DO model is verified in terms of maneuverability. Finally, simulation experiments in different scenarios show that the ANM-DO model shows lower filtering errors tracking near space hypersonic jump gliding targets, and verified the adaptability of the model proposed in this paper.INDEX TERMS maneuver model, target track, Markov model, Kalman filter.

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Section: Introductionmentioning

confidence: 99%

Near Space Hypersonic Vehicle Target Tracking Adaptive Non-Zero Mean Model

Fan¹,

Jia-jun²,

Chen³

et al. 2022

IEEE Access

Self Cite

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“…To the best of our limited knowledge, many scholars have researched the detection of HGV and the optimisation of radar resources, but these studies mainly focus on the HGV trajectory tracking and prediction [3,4], radar task scheduling [5] and radar target allocation [6,7]. There are few studies on the optimisation of radar search parameters.…”

Section: Introductionmentioning

confidence: 99%

A search method for a hypersonic gliding vehicle based on early warning information guidance

Zhang¹,

Jia-jun²,

Li³

et al. 2022

IET Radar Sonar & Navi

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The high speed and high manoeuvrability of a hypersonic gliding vehicle (HGV) pose a severe challenge to the existing early warning detection system. Optimising the search resources of a phased array radar to improve the HGV detecting efficiency has become a practical problem. In this study, a HGV search method based on a hybrid optimisation algorithm is proposed with the early warning information guidance as a priori condition. Firstly, the HGV priority judgement model is established, and the priority quantification equations for height, velocity and distance are designed. Secondly, the search parameters of the radar are optimised with the maximum cumulative detection probability, the shortest average discovery time and the highest priority level as the objective functions, and a radar search model is established. Finally, to overcome the problem that particle swarm optimisation (PSO) is easy to fall into local optimal solution, a hybrid optimisation algorithm based on differential evolution (DE) and PSO is proposed. The performance of the proposed method is verified in two simulation scenarios, and the results show that the proposed method outperforms existing mainstream search methods and can reasonably allocate search resources according to the priority of HGV.

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“…In contrast, unsupervised UDT method [12] can resolve the manual labelling problem, however it demands the platform to be very powerful and its tracking accuracy will be degraded. Generally, the tracking accuracy of the methods based on deep learning can be greatly improved, but the large computation cost or workload to label samples constrains the application of these tracking strategies in the real-time detecting and tracking field [13][14][15][16][17][18][19][20][21][22][23][24][25]. In addition, these tracking strategies are also not suitable for tracking target which is outside the training sample set.…”

Section: Introductionmentioning

confidence: 99%

“…Generally, the tracking accuracy of the methods based on deep learning can be greatly improved, but the large computation cost or workload to label samples constrains the application of these tracking strategies in the real-time detecting and tracking field [13][14][15][16][17][18][19][20][21][22][23][24][25]. In addition, these tracking strategies are also not suitable for tracking target which is outside the training sample set.…”

mentioning

confidence: 99%

Kernel correlation filter tracking strategy based on adaptive fusion response map

Xiu

2021

IET Image Processing

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Aiming at the problem that the tracking performance of the traditional kernel correlation filter tracking algorithm is easy to be affected by illumination variation, occlusion and motion blur during tracking, an improved tracking strategy is proposed. A new Histogram of Hue Gradient (HHG) feature is designed, and the new HOG-HHG feature is obtained by connecting the HOG and the HHG in series. Two features, CN and HOG-HHG, are extracted respectively, and two kernel correlation filter classifiers are constructed base on the two features above to establish the corresponding response maps of the tracking scenes, respectively. The response maps are fused adaptively to improve the tracking robustness to the complex situations in the tracking process. The updating strategy of the target model is designed based on peak sidelobe ratio (PSR) and its difference, and the adaptive thresholds are used to improve the stability of the target model. Simulation results show that the proposed method has better tracking adaptability to the illumination variation, occlusion and motion blur. Both the precision and the success rate can be enhanced. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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A Damped Oscillation Model for Tracking Near Space Hypersonic Gliding Targets

Cited by 19 publications

References 18 publications

Near Space Hypersonic Vehicle Target Tracking Adaptive Non-Zero Mean Model

Near Space Hypersonic Vehicle Target Tracking Adaptive Non-Zero Mean Model

A search method for a hypersonic gliding vehicle based on early warning information guidance

Kernel correlation filter tracking strategy based on adaptive fusion response map

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