Raytheon Company

Hughes Aircraft Company

Samuel S Blackman

Robert J Dempster

Douglas E Carroll

Rachel B Norman

Stefan J Schwoegler

Stephen A Capparelli

Robert A Rosen

Keian Christopher

Nicholas J Ploplys

Ray B Huffaker

Thomas S Nichols

Brian A Cronin

Justin Ng

Ephrem S Paredes

Katherine K Cheung

Loretta A Testa

Catherine Durand

Kristine Hacobian

Catherine Pickle

Douglas B Tyler

Radar system that utilizes Multiple Hypothesis Tracker (MHT) to resolve angle ambiguities, from a series of dwells with ambiguous detections over time. The system receives first and second observation, forms radar tracks and ambiguous angle detections using unfolding data at each of the ambiguous angle detections, scores the radar tracks to determine a best hypothesis of tracks, where a hypothesis for the MHT is formed by collecting compatible tracks into the hypothesis and computing probabilities of the hypothesis by using the score of each radar track in said hypothesis, and compares the scores of all the radar tracks originating from the first observation data to determine whether one of the scores of the radar tracks exceeds the scores of all other radar tracks originating from the same first observation data by a predetermined range.

Resolving radar angle ambiguities using a multiple hypothesis tracker

A system and method for tracking an object receive electronic intelligence (ELINT) track information related to the object and radar track information. A first likelihood that the radar track information is also related to the object is determined at a first time of the ELINT track information and a first time of the radar track information. A second likelihood that the radar track information is also related to the object is determined at a second time of the ELINT track information and a second time of the radar track information. The first likelihood and the second likelihood are processed to determine whether the ELINT track information and the radar track information should be associated as both being related to the object.

Apparatus and method for processing electronic intelligence (ELINT) and radar tracking data

Aspects of the present invention relate to a system () and a method for tracking one or more targets by a radar using a multiple hypothesis tracking (MHT) algorithm, the method including operating the radar to transmit a radar beam from a first location toward the one or more targets, operating the radar to receive a plurality of return signals at the first location from the one or more targets, and to generate a plurality of observations for a single radar dwell respectively corresponding to the plurality of return signals, and processing the plurality of observations in accordance with the MHT algorithm for at least two passes such that more than one of the plurality of observations are associated with a single track of the one or more targets.

Systems and methods for tracking targets by a through-the-wall radar using multiple hypothesis tracking

Embodiments described herein are directed to multiple hypothesis systems and methods for tracking observations that are domain agnostic and involves determining the probability that a given set of observations (i.e., a track) corresponds to a particular target, object or linked set of events. One embodiment described herein relates to cyber security tracking methods and systems.

Multiple hypothesis tracking

Methods for resolving radar ambiguities using multiple hypothesis tracking are described. One such method includes (a) choosing a single waveform for each of a plurality of dwells of a first scan, wherein the single waveforms of consecutive scans are different, (b) generating the first scan using the single waveform for each of the dwells of the first scan, (c) receiving observation data as a result of the first scan, the observation data comprising measured positions of true targets and false targets, (d) generating, using multiple hypothesis tracking, position predictions for true targets and false targets, (e) comparing the predicted positions and measured positions, repeating (a)-(e) until a preselected process condition is met, and determining the true targets based on the results of the comparisons.

Methods for resolving radar ambiguities using multiple hypothesis tracking

A method for measuring sensor bias and a method for estimating sensor bias is provided. Road location data is obtained. Sensor observation data is obtained. A sensor observation is identified that corresponds to an on-road target moving on a known road. A measurement of one-dimensional sensor bias is formed. As one-dimensional sensor bias measurements accumulate, multi-dimensional sensor bias is estimated. Sensor bias estimates may then be incorporated into a multiple hypothesis tracker system.

Sensor bias estimation for multiple hypothesis tracker

A method for automatic group tracking detects target formations and group tracks corresponding to each formation. Pseudo-observations are formed to represent missing observations in each track group. The pseudo-observations update the track states of undetected targets. Track validity estimates eliminate false tracks resulting from series of pseudo-observations. A group average velocity applied to each track in the group helps to maintain velocity stability. The operator has the option of suppressing the display of all tracks except for the leader of each group to eliminate the distraction of intra-group switching. This method can be applied to trackers that maintain a single track for each target or to trackers that maintain multiple track branches on each target, such as MHT.

Group tracking

A multiple hypothesis tracking system (10) which generates a substantially continuous output to a system user. The multiple hypothesis tracking system (10) generates a primary set of tracks (12) which best represents the expected number of targets of interest in a cluster. For multiple sensor applications, a secondary set of tracks is generated having a less probability than the tracks in the primary set. A knowledge of track data is maintained from one scan to a subsequent scan such that tracks can be merged and deleted (14). A universal track file (16) is generated in which track associations from one scan to a subsequent scan are correlated such that the output of the track file remains consistent with respect to the number of tracks.

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Los Angeles, CA, United States of America

Samuel S Blackman