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雷达和声纳里目标位置的估计是指在有噪声和杂波的情况下同时估计距离和角度。最大似然位置估计的总体特性和系统抑制杂波的能力可用距离角度模糊函数来描述。该函数取决于信号波形和阵列外形,即取决于系统的时间特性和空间特性。 模糊分析和方差限分析指出:系统带宽往往可以换取阵列尺寸;方向相关信号可用来获得较好的角度分辨力而勿须增加阵列尺寸;宽带方向相关信号(时间分集)可换取大的真实阵列或假想阵列(空间分集)。这种换取(折衷)办法显然被某些动物的回声定位系统所利用。 上述见解主要是从距离角度模糊函数的性质得来。一般来说,对于任何最大似然参数估计的设计和计算,一个适当的模糊函数都是非常有用的。例如,采用多参数模糊函数体积的极小化法可以得到最优的系统识别法和最佳的无线电导航系统。
The estimation of the target position in radar and sonar refers to the simultaneous estimation of distance and angle in the presence of noise and clutter. The overall characteristics of maximum likelihood location estimation and the ability of the system to suppress clutter can be described by distance-angle ambiguity functions. The function depends on the signal waveform and the shape of the array, which depends on the time and space characteristics of the system. Fuzzy analysis and variance analysis show that: the system bandwidth can often get the size of the array; direction-related signals can be used to obtain better angle resolution without increasing the size of the array; broadband direction-dependent signals (time diversity) can be exchanged for large real array or Hypothetical array (space diversity). This exchange (trade-off) approach is apparently utilized by some animal echolocation systems. The above opinion is mainly derived from the perspective of the nature of fuzzy functions. In general, for any design and calculation of maximum likelihood parameter estimation, a suitable ambiguity function is very useful. For example, minimization of the volume of a multi-parameter ambiguous function yields the best system identification and the best radionavigation system.