Firstly, the character of multi-target detection is analyzed, the fractal theory is introduced, and then the theory of fusion detection scheme is introduced in detail.
首先对多目标检测的特点进行了分析，对分形理论进行了介绍，然后详细介绍了该融合检测算法的思路和原理。
The results indicate that this technique can improve the performance of CA and OS CFAR detection in multi target interference environments without any performance loss in homogeneous environments.
结果表明，该方法在不降低均匀环境下检测性能的条件下，可以明显改善CA和OS-CFAR在多目标干扰环境下的检测性能。
This paper presents a new small target detection approach, which is based on multi resolution distance map and background texture analysis.
本文提出了一种基于背景纹理分析和多尺度距离像分析的目标检测方法。
The simulation results show that this method is not only suitable for the detection and the parameter estimation of multi target radar echo signal, but also good at reducing noise.
仿真实验表明，该方法能有效地检测多目标雷达回波信号并准确地估计其参数，而且有较好的抗噪声性能。
Based on the detail analysis of optical flow model, a robust multi-resolution estimation approach of optical flow is proposed, and some practical problems are also discussed on target detection.
该文在分析光流模型约束条件的基础上，提出了一种鲁棒的多分辨率光流估计方法，并对光流应用于目标检测的一些实际问题进行了探讨。
This paper expatiates the notion of image fractal dimension and multi-scale fractal feature, proposes a ship target detection method based on multi-scale fractal feature.
阐述了图像分形维和多尺度分形特征的概念，提出了一种多尺度分形目标检测方法。
In this paper, a brand new multi-target trajectory tracking algorithm based on random finite set theory is brought forward by adopting classical signal detection technique along with GMPHD filter.
在该文中，各目标的航迹信息以假设形式表述，数据互联则是通过使用经典的多元假设检测方法判决假设矩阵实现。
Nowadays, studies on MIMO radar mainly focus on DOA estimation, target detection performance analysis, waveform design and multi-channel signal modeling of active radars.
目前，国内外对MIMO雷达的研究主要集中在有源mimo雷达DOA估计、目标检测性能分析和波形设计与多通道信号模型等方面。
A new adaptive constant false alarm rate (CFAR) detector, referred as stepwise cumulation CA (SCCA) CFAR detector, is presented for target detection in a multi-target environment for SAR imagery.
针对多目标环境下的SAR图像目标检测，提出一种新的自适应cfar(恒虚警)检测器。
Most CFAR detectors need prior information on interfering 'targets in a multi-target environment, and hence can not keep stable detection performance when the detection environment changes.
多数CFAR检测器在多目标检测环境下需要关于干扰目标的先验信息，当检测环境发生变化时，这些检测器很难维持稳定的检测性能。
Most CFAR detectors need prior information on interfering 'targets in a multi-target environment, and hence can not keep stable detection performance when the detection environment changes.
多数CFAR检测器在多目标检测环境下需要关于干扰目标的先验信息，当检测环境发生变化时，这些检测器很难维持稳定的检测性能。
应用推荐