Space-Based Focal Plane Ambiguous Measurement Ballistic Target MeMber Tracking

Zhao, Wei; Huang, Shucai; Cao, Wenhuan

doi:10.3390/s18113996

Cited by 2 publications

(1 citation statement)

References 26 publications

(24 reference statements)

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“…During their weightless free-flight phase, which is also the mid-segment of the flight process, warheads traverse predetermined orbits. Therefore, this segment also serves as a pivotal research area for orbit tracking and determination within early warning systems [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Multi-Sensor Joint Tracking Algorithm with Unknown Noise Characteristics

Sun,

Wang,

Diao

et al. 2024

Sensors

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In this study, to solve the low accuracy of multi-space-based sensor joint tracking in the presence of unknown noise characteristics, an adaptive multi-sensor joint tracking algorithm (AMSJTA) is proposed. First, the coordinate transformation from the target object to the optical sensors is considered, and the observation vector-based measurement model is established. Then, the measurement noise characteristics are assumed to be white Gaussian noise, and the measurement covariance matrix is set as a constant. On this premise, the traditional iterative extended Kalman filter is applied to solve this problem. However, in most actual engineering applications, the measurement noise characteristics are unknown. Thus, a forgetting factor is introduced to adaptively estimate the unknown measurement noise characteristics, and the AMSJTA is designed to improve the tracking accuracy. Furthermore, the lower bound of the proposed algorithm is theoretically proved. Finally, numerical simulations are executed to verify the effectiveness and superiority of the proposed AMSJTA.

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Section: Introductionmentioning

confidence: 99%

Adaptive Multi-Sensor Joint Tracking Algorithm with Unknown Noise Characteristics

Sun,

Wang,

Diao

et al. 2024

Sensors

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A method for calculating the discovery time of ballistic missiles detected by an infrared early warning satellite

2023

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To determine the high dynamic change characteristics of the relative space position between a ballistic missile and an early warning satellite during detection, a centric motion model of the ballistic missile and the early warning satellite are established first. Then, the space geometric relationship is presented. Based on the gray body radiation characteristics, the calculation model of the infrared radiation characteristics of the ballistic missile in the boost phase is established. Then, a method of early warning satellite detection and discrimination considering geometric visibility and infrared visibility is proposed. Finally, the simulation and key factor comparison analysis are carried out with a typical early warning satellite, infrared detector, and ballistic missile data. Validation results show that this method can quickly and accurately calculate the discovery time and flight height of ballistic missiles detected by early warning satellites. The validation results reveal that the missile trajectory and detection bands have a significant effect on the discovery time, and the discovery time in the 2.7 µm band is earlier than that in the 4.3 µm band for the same missile trajectory. It is also found that the change in SNRth between 4.24 and 7.58 has limited influence (less than 2 s) on the discovery time. The research conclusions have important significance for improving the detection strategy of ballistic missile defense. It can also provide support for optimizing missile trajectories.

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Space-Based Focal Plane Ambiguous Measurement Ballistic Target MeMber Tracking

Cited by 2 publications

References 26 publications

Adaptive Multi-Sensor Joint Tracking Algorithm with Unknown Noise Characteristics

Adaptive Multi-Sensor Joint Tracking Algorithm with Unknown Noise Characteristics

A method for calculating the discovery time of ballistic missiles detected by an infrared early warning satellite

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