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Open Access Issue
Application of improved augmented radial basis functions in optimization design of long-range guided rocket
Journal of National University of Defense Technology 2025, 47(6): 145-156
Published: 01 December 2025
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Objective

Since its inception, the long range guided rocket (LGR) has demonstrated powerful capabilities in various combat scenarios and has become one of the weapon systems that countries are competing to develop. Compared to tactical missiles, long-range guided rockets have lower costs and have a range, lethality, and strike accuracy far beyond conventional rockets. They have been widely integrated into modern weapon and equipment systems. With the improvement of weapon modernization level, the demand for high-performance, low-cost, and highly reliable design of long-range guided rockets is becoming increasingly urgent, which puts forward higher requirements for existing design methods. Remote guided rockets are complex systems composed of multiple subsystems, and their design process is characterized by multidisciplinary, strong coupling, nonlinearity, and high time consumption. However, the existing optimization design methods combined with complex multidisciplinary simulation models have low efficiency, which greatly limits the engineering applicability of remote guidance rocket optimization design. Therefore, reducing computational complexity and improving overall design optimization efficiency through approximate modeling techniques are of great significance for enhancing the performance of long-range guided rockets.

Methods

The sequence approximation optimization method was widely used in the optimization design of high time-consuming simulation models. The following proposed a sequence approximation optimization method based on improved augmented radial basis, which included experimental design, approximation modeling, and sequence sampling. The experimental design method was applied to generate a small number of samples to establish an initial approximate model with relatively low accuracy. The training set was gradually expanded by adding new samples, and the approximate model was dynamically updated. Adding sample points can not only verify the accuracy of existing approximate models, but also gradually improved the model accuracy, thereby achieving efficient prediction of the global optimal solution.

Results

The sequence approximation optimization results converge after approximately 620 iterations. Through optimization, the range increased from the initial 940 km to 1097 km, an increase of about 16.7%, and the total engine weight decreased from 4400 kg in the initial plan to 4373 kg. The length of the optimized design cone has significantly increased, and the installation position of the tail wing has moved forward from the half span position, resulting in improved aerodynamic performance. In the parameters of the power system, the increase in the width of the propellant column wing is used to obtain a larger burning surface and improve engine thrust, while other parameters do not change significantly; In the flight trajectory parameters, the launch speed inclination angle slightly increases, and there are significant changes in the angle of attack sequence. The maximum flight altitude of the guided rocket has been increased to around 100km, with a slight increase in engine thrust, a slight increase in landing angle and terminal Mach number, a significant increase in maximum normal overload, and a small change in dynamic pressure. The changes in flight performance are consistent with the results of parameter analysis.

Conclusions

Established an overall performance analysis model for remote guided rockets. Construct an overall performance calculation model for remote guided rockets based on disciplines such as geometry, aerodynamics, mass, dynamics, and ballistics, provide an initial plan, and complete trajectory simulation. A sequence approximation optimization method based on improved augmented radial basis function was proposed. The efficiency of approximation modeling was improved through recursive evolution experimental design and fast cross validation, and adaptive sampling was performed based on non-precise strategies. The numerical results showed that the proposed method had significant advantages. For the multidisciplinary optimization problem of remote guided rockets, the proposed method was adopted to obtain an optimized design scheme that satisfies constraints and has superior performance. The range increased from the initial design of 940 km to 1097 km, an increase of about 16.7%.

Open Access Issue
Multi-spacecraft cooperative guard strategy based on reachable domain coverage
Journal of National University of Defense Technology 2024, 46(3): 12-20
Published: 28 June 2024
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Aiming at guarding high-orbit high-value targets, a multi-spacecraft cooperative guard strategy based on reachable domain coverage was proposed. The cooperative guard mission was described from the perspective of relative motion, and the multi-pulse reachable domain of the threat was modeled as a convex optimization problem. In the framework of receding optimization, the guard planes and points were designed based on the dynamically updated terminal reachable domain of threat, and a multi-spacecraft cooperative trajectory planning model was constructed with the guard points as terminal position constraints, the corresponding guard trajectories were generated. Simulation results show that the proposed method can quickly calculate the terminal reachable domain of the threat. The cooperative guard strategy can effectively prevent the threat in multiple scenarios, and the guard success rate increases with the enhancement of the maneuvering ability of the guard spacecraft.

Open Access Issue
Multi-sensor cooperative planning of space objects detection
Journal of National University of Defense Technology 2024, 46(4): 37-44
Published: 28 August 2024
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Background of collaborative detection of space targets by multiple ground-based radars, to solve the issue of low detection efficiency in traditional collaborative planning methods that use the entire detectable arc segment as the decision variable, a multi-sensor collaborative detection scheduling model was established, and an adaptive immune genetic algorithm that could simultaneously determine the detection arc segment and detection start time was proposed. Considering various factors such as the space objects attribute, type, launch time, radar cross-section grade, and purpose, a multi-level fuzzy comprehensive evaluation model was constructed, and the 1-9 scale method was adopted to obtain the priority of the spatial target. In order to maximize the priority, consideringvarious constraints such as detection time, sensor capacity, and so on, an adaptive immune genetic algorithm was used to solve the problem. The performance of the planning method was evaluated from two aspects of detection resource consumption rate and task completion rate. By comparative analysis with the improved heuristic algorithm and traditional evolution algorithm, this algorithm improves the task completion rate while also reducing resource consumption rate.

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