单脉冲相控阵雷达通道不一致性校正方法研究
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摘要
在采用单脉冲技术对目标进行角度测量的相控阵雷达系统中,和差波束接收通道的幅相不一致性对系统的角度测量精度有较大的影响。
    对和差接收通道的幅相校正技术理论上分为两类:离线校正方法和在线校正方法。离线校正的方法是现阶段单脉冲雷达系统进行和差通道幅相校正采用的主要方法,它通过注入测试信号的方法来得到对误差接收通道幅相特性的估计。因为离线校正可以确知输入信号的充分信息,这样得到误差系统的特性从原理与计算上来讲是不复杂的。文章第四章针对离线校正的思路与算法作了详细地介绍,比较了三种离线校正算法在不同的误差模型与噪声模型中对和差接收通道校正后角度测量精度变化的情况。离线校正的缺点是适应性不强,它不能对变化的误差系统进行实时跟踪,并且它很依赖于注入测试信号的形式。
    在线算法不需要测试信号且可以实时地对误差模型进行跟踪,有着良好的应用前景,但由于其实现的复杂性、雷达回波信号的多样性,使得人们极少涉及这个领域。随着非线性系统回归和系统识别技术的发展,在线识别与校正领域又活跃起来了。文章的第五章介绍了基于非线性回归和系统辨识模型的校正思路和校正方法,通过大量的仿真分析算法在不同的误差模型、信噪比条件下对和差通道的幅相校正对角度测量精度的影响,给出了仿真结果与结论。最后,对全文作了总结。
Inconsistency between the sum and difference channels in the phased array radar system will affect angle measurement accuracy if the monopulse angle measurement technique is employed. In order to achieve better angle measurement accuracy, they need to be calibrated.
    The calibrating technology is mainly divided into two groups: the off-line ones and the on-line ones. The former one is now widely used in the monopulse system to calibrate the amplitude and phase imbalances between the sum and difference channels by injecting test signals. Because we can have a full knowledge of the input signal, the conception and realization of this idea is not too complicated. Chapter Four is focused on this and it gives us a very detailed introduction to the calibrating idea and algorithm realizations. It also introduces the calibrating performances by using three different off-line calibrating algorithms along with the simulation results. The deficiencies of the off-line methods are as follows: it is not an adaptive method so it cannot change when the system parameter changes; it is, to some degree, depend on the form of the injecting signal.
    Owing to the complexity of the on-line methods and the diversity of the form of radar echo wave, there aren't many people who have paid much attention to this question of on-line calibrating. But along with the development of nonlinear regression and system identification, on-line detection and calibrating gained their former attention. Chapter Five in details introduces the on-line calibrating idea and method based on nonlinear regression and system identification. It also analyses the performance characteristics of this methods under two different error systems while at last gives us the simulation results. Finally, a summary is given.
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