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The probabilistic multi-hypothesis tracking (PMHT) algorithm has been successfully applied to a simulated multi-static active sonar data set that contains a single constant velocity target in varying amounts of clutter [1]. The simulated data set in that study contained negligible registration error was therefore easily registered to a common frame of reference for use in a centralized tracking architecture...
Feature aided tracking can often yield improved tracking performance over the standard radar tracking with positional measurements alone. However, the complexity of the tracker may dramatically increase due to the inclusion of the target feature state. In this paper, we study the situation where the target feature is a constant or slowly varying parameter with respect to the target state and can be...
The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian algorithm for estimating multiple target states with varying target number in clutter. In the present work, it is shown that a missed detection in one part of the field of view has a significant effect on the probability hypothesis density (PHD) arbitrarily far apart from the missed detection. In the case of zero...
In this contribution the problem of tracking convoys moving on the ground by means of airborne radar is discussed. A coherent radar with multi-channel array antenna is considered which makes clutter suppression by space-time adaptive processing (STAP) techniques possible. In addition, a technique to estimate the lateral length component of a convoy is used in addition to the conventional range measurement...
For the detection of targets moving on ground, airborne ground moving target indicator (GMTI) radar is well-suited. In the tracking process, complex target dynamics, particularly stop and go maneuvers, and target masking due to Doppler blindness, often lead to track losses. By means of a refined sensor model it is possible to detect and handle such diverse target states. In addition, the generation...
NURC has developed a high-performance, computationally-efficient, flexible, and robust fusion and tracking capability for undersea surveillance, with extensive simulation-based and sea-trial testing. This paper documents recent experimental results, based on simulated datasets developed for common analysis under the auspices of the Multistatic Tracking Working Group (MSTWG), as well as real datasets...
Target tracking algorithms operate in an environment of uncertain measurement origin. Targets are randomly detected, and clutter measurements from unwanted random scatterers are present. A vast majority of target tracking algorithms have been developed with the assumption of infinite sensor resolution, where a measurement can have only one source. This assumption is not valid for real sensors, such...
Ground targets are constrained on the Earth with their velocity vector direction aligned mostly along the body longitudinal axis. The pose angle therefore carries kinematic information useful for tracking maneuvering targets. For target identification (ID), range profiles obtained by a high range resolution (HRR) radar are compared with reference templates in pose angle per target class, thus producing...
In this paper, a two-tier hierarchical architecture is proposed to address the multi-target tracking problem using a particle probability hypothesis density filtering algorithm. According to a proposed cluster scheduling method, the base station selects active clusters at each time step and determines their order for the sequential data fusion in the second level of hierarchy. Within each active cluster,...
The multitarget intensity filter is derived from a Bayesian first principles approach using a Poisson point process approximation at one step. The prior multitarget model is assumed to be a Poisson point process. The Bayes multitarget posterior probability density function is first defined on the Poisson event space, and then reformulated in terms of the intensity functions that characterize all Poisson...
Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic multiple hypothesis tracking (PMHT) is an efficient approach for dealing with it. Essentially, PMHT is based on expectation-maximization for handling association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodology. However,...
A promising line of research attempts to bridge the gap between radar detector and radar tracker by means of considering jointly optimal parameter settings for both of these subsystems. This approach, which can also be considered as a form of feedback from the tracker to the detector results in an adaptive radar system. In the present work, we attempt to move in a direction to fulfill this promise...
The problem of tracking targets, where measurements may occasionally be masked by the Doppler blind zone of the sensor, arises in Ground Moving Target Indicator tracking and aerial surveillance. For such problems, no target return is registered when the range rate (Doppler) of the target falls below a sensor-specific threshold in magnitude. For this reason, possible missed detections provide kinematic...
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