多发弹气动参数联合辨识方法研究

利用局部优化算法对多发弹测量数据进行气动参数辨识，可能存在局部最优解，且同一气动参数多发弹的辨识结果有时差异较大。为提高弹丸气动参数辨识的准确性与合理性，提出一种同时 利用多发弹测量数据进行联合辨识的全局优化策略。该策略采用局部优化算法获得搜索空间，将弹丸飞行的稳定性条件作为约束条件，利用最小二乘准则构建准则函数，应用差分进化算法对多发弹数据同步全局寻优，从而获得唯一的全局最优解。以某大口径榴弹纸靶试验数据为例对所提方法进行了验证，结果表明：相比于现有的辨识策略，所提策略计算出的准则函数值更小，重构弹道结果与测量值更接近，且计算稳定性较好。

Research on Combined Aerodynamic Parameters Identification Using Flight Data of Multiple Projectiles

It may run the risk of becoming trapped into a local minimum when local optimization algorithms are used to identify the aerodynamic parameters of multiple projectiles. And the identified results of the same aerodynamic parameter obtained from multiple projectiles are usually discrepant. A global optimization strategy using multiple flight test data for aerodynamic parameters identification is proposed to improve the accuracy and reasonableness of aerodynamic parameters identification for projectiles. A sole global optimal solution can be achieved by obtaining the search space with local optimization algorithm, taking the flight stability of projectiles as the constraint, establishing the cost function by the use of least-square principle, and applying the differential evolution algorithm to the simultaneous global optimization problem for multiple projectiles. The proposed strategy is validated by processing the yaw-card data of a certain large-caliber projectile. The results indicate that, compared to the identification strategies in the current research literature, the proposed strategy is of smaller cost function value and better computational stability, making the reconstructed trajectory closer to the actually measured one.Key