论文标题
在使用粒子滤波器中以一系列图像框架检测到低SNR对象之前的轨迹
Track Before Detect of Low SNR Objects in a Sequence of Image Frames Using Particle Filter
论文作者
论文摘要
在本信中简要研究了基于噪声和混乱的情况下基于图像帧序列的低信号与噪声比（SNR）对象检测和跟踪低信号与噪声比（SNR）对象的多个模型轨道检测（TBD）粒子过滤器的方法。在收到图像框架后的每个时间实例，首先，将一些预处理方法应用于图像。然后，将其发送到多个模型TBD粒子滤波器以检测和跟踪对象。评估该方法的性能，以在不同的情况下检测和跟踪对象，包括噪声和混乱。
A multiple model track-before-detect (TBD) particle filter-based approach for detection and tracking of low signal to noise ratio (SNR) objects based on a sequence of image frames in the presence of noise and clutter is briefly studied in this letter. At each time instance after receiving a frame of image, first, some preprocessing approaches are applied to the image. Then, it is sent to the multiple model TBD particle filter for detection and tracking of an object. Performance of the approach is evaluated for detection and tracking of an object in different scenarios including noise and clutter.
