在未知瞬态信号检测中，一般采用广义似然比检测。
To detect unknown signals, we usually use the generalized likelihood ration test (GLRT).
本文提出了一种利用广义似然比检测图象边缘的算法。
In this paper, We present an edge detection algorithm using generalized likelihood ratio.
然而广义似然比检测不能有效利用瞬态信号的固有特性，检测性能不是很好。
However, the performance of the GLRT is not very good since it does not adequately use the intrinsic characteristic of transients.
狭义最大似然比检测算法(GLR)非空时自逆当信号处放的比拟典型的算法。
Generalized maximum likelihood ratio detection algorithm (GLR) is a typical method of space-time adaptive signal processing.
传统信号检测理论和方法主要采用似然比检测，已得到广泛的应用，但是存在明显的缺点。
The traditional signal detection theory and method using likelihood ratio test has been used widely, but it has obvious drawbacks.
为了进一步从通过相关检测门限的像素中检测出目标，又提出了一种新的广义似然比检测方法。
In order to further the targets detection in these few pixels, an improved GLRT method is developed.
时间扩展信道(TSD)是信道畸变的一种常见形式，它的最佳似然比检测器是副本相关积分器(RCI)。
The optimum LRT detector of time spreading dispersion channel, a familiar channel dispersion form, is replica correlation integrator (RCI).
然后基于时域差分模型提出了红外慢速小目标时域检测算法，算法共分为两步：相关检测和广义似然比检测。
Then based on the temporal difference models, we formulate the detection problem in 2 steps, correlation detection and generalized likelihood ratio test (GLRT).
该方法首先对各距离分辨单元在方位向进行非相参积累，然后利用类似单个脉冲下扩展目标的广义似然比检测器来实现高分辨率雷达的检测。
First, each range resolving unit was accumulated non-inherently in azimuth, and then the detection of HRR target was done with the GLRT detector similar to that of the mono-pulse spread targets.
文中根据检测似然比序列的特点，利用递推关系，提出了一种快速算法。
Based on the characteristics of the detection likelihood ratio sequence and the recursive relations, a fast algorithm is proposed.
分组判决算法利用检测窗内所有数据帧，在广义似然比准则下对相关模板进行联合估计，进一步压制了模板噪声。
The group decision algorithm based on GLRT principle was utilized to estimate correlation template through all data frames in detection window and could offer better noise suppression.
导出了杂波稳定分量相干及不相干时的似然比(LR)检测器的结构。
The likelihood ratio (LR) detector structures when the clutter steady component is coherent and noncoherent are developed respectively.
由于该算法充分利用了软译码得到的似然比信息，因此可以实现最优信号检测。
This algorithm can achieve the best demodulation because the likelihood ratio of information is used adequately.
由于该算法充分利用了软译码得到的似然比信息，因此可以实现最优信号检测。
This algorithm can achieve the best demodulation because the likelihood ratio of information is used adequately.
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