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针对基于RCS统计模型的目标检测研究在复杂航迹下的局限性,提出了一种直接利用RCS原始数据计算发现概率的新方法。首先,针对某典型隐身目标,利用FEKO获取了其在平飞和水平拐弯两种机动航迹下的RCS数据,经统计处理后与卡方分布模型拟合论证了模型拟合在复杂航迹下的局限。其次,根据目标RCS与回波幅度之间的转化关系式,推导得出同时包含距离量和RCS随机量的检测概率计算模型。最后,利用获取的RCS原始数据仿真了机动目标在两种航迹下任意时刻的发现概率。仿真结果反映了距离与目标RCS共同影响检测概率的实际,方法可为雷达与隐身目标模拟对抗提供理论支持,为提高雷达检测性能和技战术指标提供支撑。
Aiming at the limitation of target detection based on RCS statistical model under complex trajectory, a new method to calculate the discovery probability by directly using the original RCS data is proposed. First of all, for a typical stealth target, FEKO was used to obtain RCS data under two flight paths of level flight and horizontal turning. After statistical processing and chi-squared distribution model fitting, it was proved that the model fits well under complex trajectory Limitations. Secondly, according to the conversion relation between the target RCS and the echo amplitude, a calculation model of the detection probability which includes both the distance and the RCS random quantity is deduced. Finally, the probability of finding a maneuvering target at any moment under two kinds of tracks is simulated by using the obtained RCS original data. The simulation results reflect the fact that the distance and the target RCS jointly affect the detection probability. The method can provide theoretical support for radar and stealth target simulation and provide support for improving radar detection performance and technical and tactical indicators.