Samuel S. Blackman

Multiple hypothesis tracking for multiple target tracking

Multiple hypothesis tracking (MHT) is generally accepted as the preferred method for solving the data association problem in modern multiple target tracking (MTT) systems. This paper summarizes the motivations for MHT, the basic principles behind MHT and the alternative implementations in common use. It discusses the manner in which the multiple data association hypotheses formed by MHT can be combined with multiple filter models, such as used by the interacting multiple model (IMM) method. An overview of the studies that show the advantages of MHT over the conventional single hypothesis approach is given. Important current applications and areas of future research and development for MHT are discussed.

IMM/MHT solution to radar benchmark tracking problem

The benchmark problem addresses the efficient allocation of an agile beam radar in the presence of highly maneuverable targets and radar electronic countermeasures (ECM). This paper presents methods for applying an interacting multiple model/multiple hypothesis tracking (IMM/MHT) tracker to this radar tracking and resource allocation problem. The manner in which IMM/MHT tracking and data association methods lead to efficient agile beam radar allocation is discussed and results showing that this approach is more efficient than previously proposed methods is presented. However, results indicate that the presence of ECM requires that the allocated signal-to-noise ratio (SNR) be increased and the allowable track position uncertainty be decreased from the values that would be chosen to minimize energy allocation when no ECM is present.

Multiple hypothesis track confirmation for infrared surveillance systems

An overall methodology is described for the application of a multiple hypothesis tracking (MHT) algorithm to the infrared (IR) surveillance system problem of establishing tracks on dim targets in a heavy clutter or false alarm background. The authors discuss the manner in which the detection and tracking systems are jointly designed to optimize performance. They present approximate methods that can conveniently be used for preliminary system design and performance prediction. They discuss the use of a detailed Monte Carlo simulation for final system evaluation and present results illustrating the proposed methods and comparing predicted and simulation performance. >

Application of IMM filtering to passive ranging

This paper presents an interacting multiple model (IMM) filtering scheme for use in passive ranging with angle-only measurement data. The application is to an air-to-air multiple target tracking environment. The IMM implementation uses the Modified Spherical Coordinates (MSC) method for one of the filter models and a general acceleration model for the other filter. This method, in effect, provides maneuver detections to that range and range rate estimation errors from the MSC filter are minimized and an accurate covariance matrix is maintained to reflect these errors.

Demonstration of multiple-hypothesis tracking (MHT) practical real-time implementation feasibility

Since its initial definition, about 25 years ago, the potential data association performance enhancements associated with Multiple Hypothesis Tracking (MHT) have been widely accepted. However, the actual practical implementation of MHT has been impeded by the perception that its complexity precludes real-time application. The purpose of this paper is to show that modern computational capabilities and newly developed MHT algorithm efficiencies make real-time MHT implementation feasible even for scenarios with large numbers of closely spaced targets. The paper begins by outlining the elements of our MHT algorithm and by defining a typical stressing scenario, with about 100 closely spaced targets, which is used for evaluation of real-time MHT implementation capability. It then presents the processing times required for each of the MHT algorithm elements on a 866Mhz Pentium III computer. Finally, it also presents the memory requirements. Conclusions are that real-time implementation is currently feasible for typical stressing scenarios using the 866Mhz Pentium III computer or other similar modern machines. The extension to larger scenarios with future computer systems is outlined.

Application of multiple-hypothesis tracking to agile beam radar tracking

This paper describes methods that have been developed for using multiple hypothesis tracking (MHT) for an agile beam radar in the presence of range gate pull off (RGPO) electronic countermeasures (ECM). The paper shows how the agile beam radar allocation logic can be extended to include uncertainty in target position due to data association uncertainty. It also shows how the MHT track score can be modified to reflect target offset from the commanded radar antenna position and how measured SNR is included in the track score. Results from the second Benchmark tracking study are presented. These results show MHT-based allocation to ge highly efficient. The results also show that the system satisfies stringent track maintenance requirements in the presence of RGPO and coincident target maneuvers.

Improved tracking capability and efficient radar allocation through the fusion of radar and infrared search-and-track observations

The benchmark problem addresses the efficient allocation of an agile-beam radar in the presence of highly maneuverable targets and radar ECM. The multisensor benchmark tracking solution is aided by the presence of a scanning infrared search-and-track (IRST) system. This paper presents methods for applying a tracker with interacting multiple- model (IMM) filtering and multiple-hypothesis tracking (MHT) data asso- ciation to this multiple-sensor tracking and resource allocation problem. It presents a hybrid multisensor tracking architecture in which an IMM- MHT tracker operating on IRST data provides the global IMM-MHT tracker with selected observations. Simulation results quantify the poten- tial improvement from the use of advanced tracking methods and IRST data to enhance agile-beam radar tracker capability.

IMM/MHT solution to radar multisensor benchmark tracking problems

The benchmark problem addresses the efficient allocation of an agile beam radar in the presence of highly maneuverable targets and radar ECM. The multisensor benchmark tracking solution s aided by the presence of a scanning IRST. This paper presents methods for applying an IMM/MHT tracker to this multiple sensor tracking and resource allocation problem. The paper discusses the manner is which IMM/MHT tracking and data association methods lead to efficient agile beam radar allocation and presents results showing that this approach is significantly more efficient than previously proposed methods when only radar data are used. It presents a hybrid multisensor tracking architecture in which an IMM/MHT tracker operating on IRST data provides the global IMM/MHT tracker with selected observations. Simulation results quantify the potential improvement from the use of advanced tracking methods and IRST data to enhance agile beam radar tracker capability.

IMM/MHT applications to radar and IR multitarget tracking

Interacting multiple model (IMM) filtering and multiple hypothesis tracking (MHT) represent the most accurate methods currently available for tracking multiple maneuvering targets in cluttered environments. Although these methods are complex, modern computational capabilities make their combined implementation feasible for modern tracking systems. This paper discusses alternative approaches for developing a combined IMM/MHT tracking system and describes specific implementations that have been developed for radar and IRST applications. Simulation results for both radar and IRST systems are presented. Track maintenance and accuracy performance for the IMM/MHT system is compared with that obtained from an MHT tracker using a conventional filtering approach. Results indicate that the improvements in data association derived from the use of IMM filtering with MHT may be comparable to the well known IMM improvements in track accuracy. The addition of multiple filter models to MHT data association has the potential to significantly increase computational requirements. Thus, several compromises, described in this paper, have been developed in order to assure computational feasibility. Preliminary estimates of computational requirements are given in order to demonstrate implementation feasibility.

Application of multiple-hypothesis tracking to shipboard IRST tracking

This paper describes the use of multiple hypothesis tracking (MHT) for the IRST Shipboard Self Defense application. This application features a highly variable clutter background, such as produced by sun glint, and maneuvering targets. The paper presents a technique for including features, such as measured SNR, in the track score. Performance results are presented for the case of a simulated missile target inserted in an ocean background. The paper presents computer timing and sizing results to show that recently developed algorithm efficiencies and computational capabilities make real-time MHT tracker operation feasible within the near future. A comparative study of track maintenance shows the significant potential performance improvement of MHT when compared with other data association methods.