摘要
雷达干扰效果评估可以转化为多分类问题进行解决。对影响雷达干扰效果因素进行分析,选取雷达干扰效果评估指标,给出评估指标计算方法,在此基础上,提出应用AdaBoost组合分类模型对雷达干扰效果进行评估。以RBF神经网络作为基分类模型,采用AdaBoost M1算法训练组合分类模型,并进行实验验证。结果证明,采用组合分类模型对雷达干扰效果进行评估是可行的,并且能够得到理想的效果。
The radar jamming effect evaluation can be solved by translating it into multi-class classification problems. Firstly, the factors which influence radar jamming effect are analyzed, the evaluating indicators that influence radar jamming effect are chosen, and the measure- ments are provided. Based on these, the AdaBoost combined classification model is proposed to evaluate radar jamming effect. In the end, taking RBF neural network as its base classification model, the AdaBoost M1 algorithm is used to train the combined classification model and experiments are carried out for verification. The result shows that using combined classification model to evaluate radar jamming effect is feasi- ble for it can achieve satisfactory result.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第1期69-72,共4页
Computer Applications and Software
