Application of Dot Product for Track-before-detect Tracking of Noise Objects
نویسندگان
چکیده
The Track-Before-Detect (TBD) algorithms are applied for the tracking of signals below the noise floor. The noise object is the signal that has noise samples only. The processing of such signal using Spatio-Temporal TBD is not possible directly. The proposed preprocessing technique allows analysis of the signal using moving window approach and dot product calculations. Two vectors, related to the distributions, are compared: the overall signal and the local, related to the window position. The Monte Carlo tests are applied for the analysis of performance.
منابع مشابه
Performance of Dot-product preprocessing for Track-Before-Detect tracking of noise objects
Track-Before-Detect (TBD) algorithms are applied for the tracking of signals below the noise floor. The noise object is the signal that has noise samples only. The processing of such signal using Spatio-Temporal TBD is not possible directly. The preprocessing technique based on the window approach and dot-product calculations emphasis the differences between global and local empirical distribut...
متن کاملA Novel Method for Tracking Moving Objects using Block-Based Similarity
Extracting and tracking active objects are two major issues in surveillance and monitoring applications such as nuclear reactors, mine security, and traffic controllers. In this paper, a block-based similarity algorithm is proposed in order to detect and track objects in the successive frames. We define similarity and cost functions based on the features of the blocks, leading to less computati...
متن کاملMoving Vehicle Tracking Using Disjoint View Multicameras
Multicamera vehicle tracking is a necessary part of any video-based intelligent transportation system for extracting different traffic parameters such as link travel times and origin/destination counts. In many applications, it is needed to locate traffic cameras disjoint from each other to cover a wide area. This paper presents a method for tracking moving vehicles in such camera networks. The...
متن کاملBackground noise distribution for noise object tracking in Track-Before-Detect systems using minimal chi-square statistic
Tracking of the noise signal in noise measurements needs special techniques. The difference between object and background noise is defined, using the noise distribution. The proposed technique is based on the model of the background noise. The window based approach is used for input signal preprocessing. The comparison of two distributions empirical and observed is used. The global distribution...
متن کاملNonstationary EO/IR Clutter Suppression and Dim Object Tracking
We develop and evaluate the performance of advanced algorithms which provide significantly improved capabilities for automated detection and tracking of ballistic and flying dim objects in the presence of highly structured intense clutter. Applications include ballistic missile early warning, midcourse tracking, trajectory prediction, and resident space object detection and tracking. The set of...
متن کامل