神经网络在靶场动态精度预测射击精度中的应用

Application of Neural Networks to Predicting Firing Accuracy Using Dynamic Accuracy in Range Test

在靶场,动态精度试验可以得到较为充分的样本量,射击精度试验样本量往往相对不足。利用动态精度预测射击精度可以增加射击精度试验样本量,不过如何利用动态精度预测射击精度,一直是靶场舰炮武器系统试验中不易解决的难题。利用神经网络技术,结合靶场试验数据,建立了动态精度预测射击精度的模型,实现了动态精度数据预测射击精度。结果表明,应用该种方法,可以增加试验结果置信度,降低靶场试验费用,对于舰炮武器系统试验具有一定的实用价值。

In range, the sample size of the dynamic accuracy test is adequate and the one of the firing accuracy is relatively insufficent. Though Making use of dyanmic accury pre-estimating firing accuracy can increase the test sample size,it is always difficult in range how to use it. This paper proposes a method that dynamic accurcy pre-estmating firing accury by using neural networks technology and test data in range. The result shows that using this technique may enhance degree of confidence for test result and reduce test expenses in range. The way has definite practical value in naval gun weapon system.