再举一个例子,图2.13a给出了与图2.8相似的多个散射目标形成的回波自相关函数,但只采用了±3°视线角范围的数据。

As another example,Fig. 2.13a shows theautocorrelation function in angle for many-scatterer targets similar to that ofFig. 2.8, using only the data for aspect angles over a range ±3°.

Figure 2.13. 对于大量散射体目标的平均自相关函数:(a)视线角自相关函数;(b)频率自相关函数Average autocorrelationfunction for many-scatterer targets: (a) angle autocorrelation functions, (b)frequency autocorrelation functions. See text for details.

图中所示的两种自相关函数是对20个不同随机目标自相关函数的平均,每个目标均由20个随机放置的5m x 10m盒形散射体组成。

Each of the twoautocorrelation functions shown is the average of the autocorrelations of 20different random targets, each having 20 randomly placed scatterers in a 5 m by 10 m box.

黑色曲线为标准视线方向上的数据自相关函数曲线(视线方向与目标5m一侧正交),而灰色曲线则是从10m一侧观察数据的数据自相关函数曲线。

The black curve isthe autocorrelation of the data around a nominal boresight orthogonal to the 5 m side of the target, while the graycurve is the autocorrelation of the data viewed from the 10-m side.

以上观察目标的角度在图2.8中分别为从右侧和顶部。

These look anglescorrespond to viewing the target nominally from the right and from the top inFig. 2.8.

在F = 10 GHz,从右侧看的视线角解相关间隔为0.34°;从顶部看的解相关间隔为0.17°。

At F = 10 GHz, theexpected decorrelation interval in angle when viewed from the right is 0.34°;while when viewed from the top it is 0.17°.

这两个视线角解相关间隔在图2.13a中以垂直虚线的形式予以标记。

These expecteddecorrelation intervals are marked by the vertical dashed lines in Fig. 2.13a.

在两个例子中,解相关间隔都选择为自相关函数的第一最小值处。

In both cases, thefirst minimum of the correlation function occurs the predicted amount of changein the aspect angle.

图2.13b为30个近似随机目标在频率上的平均自相关函数曲线。

Figure 2.13b showsthe average autocorrelation function in frequency over 30 similar randomtargets.

在这一仿真中,自相关函数并没有确定的第一最小值,而是将解相关间隔近似为第一过零点的位置。

The autocorrelationin this simulation does not have a distinct minimum, but the predicteddecorrelation intervals closely approximate the first zero crossing.

图2.9所示证明了从一个足够大的视线角间隔观察一个复杂目标,可以将RCS解相关,即,两个角度上的RCS差别非常大,几乎是完全无关的。

Figure 2.9demonstrated that viewing a complex target from a sufficiently different aspectangle will decorrelate the RCS, i.e., result in a significantly differentmeasured value.

——本文译自Mark A. Richards所著的《Fundamentals of Radar Signal Processing(Second edition)》