Method and apparatus for accurate aircraft and vehicle tracking
First Claim
1. A method of tracking targets, comprising the steps of:
- receiving in a plurality of sensors, a data signal from a target, the data signal including identification information,generating, in the plurality of sensors, a time stamp TOA indicating when the data signal is received at each of the plurality of sensors,setting a cycle end time Tend as a preset cutoff time at a central server to release a batch of queued input data to a tracking module for processing,fetching a new TOA value,comparing in a first comparing step, a TOA with Tend value and if the TOA value is later than the Tend value, performing a split track check and returning to the setting cycle end time step,if the TOA value is greater than or equal to the Tend value, calculating initial solutions of 2D multilateration equations from target track data, wherein if the initial solutions for the 2D multilateration equations fail, returning to the setting cycle end time step,if the initial solutions of the 2D multilateration equations pass, performing a data-track association test to determine whether the data-track data is associated with an existing target track, should be a new track, or should be rejected,wherein if the data is associated with an existing track, the existing track position and velocities are filtered and updated with the latest record data, fetching a new TOA data, and returning to the setting a cycle end time step,wherein if the data-track data is not associated with an existing track, creating a new track and returning to the setting a cycle end time step, andwherein if outlier data is generated, the data is rejected and returning to the setting cycle time step.
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Abstract
A direct multilateration target tracking system is provided with the TOA time stamp as an input. A technique of tracking targets with varying receiver combinations is provided. Methods of correlating and combining Mode A, Mode C, and Mode S messages to enhance target tracking in a passive surveillance system are provided. A direct multilateration target tracking system is provided by TOA tracking and smoothing. A technique for selecting best receiver combination and/or solution of multilateration equations from a multitude of combinations and/or solutions is provided. A technique for correcting pseudorange values with atmospheric conditions is provided. A technique for improving height determination for regions of poor VDOP in a 3D multilateration system is provided.
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Citations
43 Claims
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1. A method of tracking targets, comprising the steps of:
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receiving in a plurality of sensors, a data signal from a target, the data signal including identification information, generating, in the plurality of sensors, a time stamp TOA indicating when the data signal is received at each of the plurality of sensors, setting a cycle end time Tend as a preset cutoff time at a central server to release a batch of queued input data to a tracking module for processing, fetching a new TOA value, comparing in a first comparing step, a TOA with Tend value and if the TOA value is later than the Tend value, performing a split track check and returning to the setting cycle end time step, if the TOA value is greater than or equal to the Tend value, calculating initial solutions of 2D multilateration equations from target track data, wherein if the initial solutions for the 2D multilateration equations fail, returning to the setting cycle end time step, if the initial solutions of the 2D multilateration equations pass, performing a data-track association test to determine whether the data-track data is associated with an existing target track, should be a new track, or should be rejected, wherein if the data is associated with an existing track, the existing track position and velocities are filtered and updated with the latest record data, fetching a new TOA data, and returning to the setting a cycle end time step, wherein if the data-track data is not associated with an existing track, creating a new track and returning to the setting a cycle end time step, and wherein if outlier data is generated, the data is rejected and returning to the setting cycle time step. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)
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31. A direct multilateration 2-D target tracking system comprising:
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a plurality of sensors for receiving signals from an aircraft; means, coupled to the plurality of sensors, for generating time stamp data indicating when the signals are received at each of the plurality of sensors; means for generating aircraft position x-y position data and velocity by multilaterating the time stamp data; means for filtering the time stamp data using an extended Kalman Filter technique where state variables in the filter are target x-y positions and velocities, the filter based on linearized statistical target dynamics state equations and statistical measurement equations; wherein depending on the type of target movement, the dynamics state equations may be one of the two forms;
one optimized for linear constant-speed motion, and the other optimized for targets under longitudinal or lateral accelerations,wherein measurement equations are defined by time-difference of arrival equations, with random noise characterizing the error in TOA measurements.
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32. A multilateration target tracking system using varying receiver combinations, comprising:
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a plurality of sensors for receiving a first signal from an aircraft, the first signal including an address corresponding to aircraft identification; means, coupled to the plurality of sensors, for generating a time stamp indicating when the first signal is received at each of the plurality of sensors; a program memory for recording a sensor combination used in a previous track update process; and determination means for determining an optimal sensor combination for a measurement equation in an extended Kalman Filter model, wherein the determination means uses a same sensor combination as a previous measurement to improve track accuracy and smoothness, wherein if a same sensor combination as a previous measurement cannot be found, but a common subset of at least three sensors may be found in both measurements, the common subset of sensor combination is used to calculate target position, and wherein if a same sensor combination as a previous measurement cannot be found and a common subset of at least three sensors is not found in both measurement, a sensor combination with the lowest Horizontal Dilution Of Precision (HDOP) will be chosen.
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33. A multilateration target tracking system for correlating different message modes, said system comprising:
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a plurality of sensors for receiving a first signal from an aircraft, the first signal including at least one aircraft message received in one of a number of predetermined message modes; means, coupled to the plurality of sensors, for generating a time stamp (TOA) indicating when the at least one aircraft message is received at each of the plurality of sensors; a track memory system including track state variables and at least a selective recent history of aircraft messages and sensor data for the target, the selective recent history including at least one or more of TOA with sensor identification, signal strengths, and a list of sensors selected to contribute to tracking solutions, wherein stored aircraft messages in the track memory system are retrieved and compared with new aircraft target messages to correlate different messages in different message modes to a single target.
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34. A direct multilateration 2-D target tracking system comprising:
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a plurality of sensors for receiving signals from an aircraft; means, coupled to the plurality of sensors, for generating time stamp data indicating when the signals are received at each of the plurality of sensors; means for generating aircraft position x-y position data and velocity by multilaterating the time stamp data; and means for filtering the time stamp data using an extended Kalman Filter technique where state variables in the filter are pseudoranges and x-y velocities as state variables in an extended Kalman filtering model.
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35. A multilateration target tracking system comprising:
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a plurality of sensors for receiving a first signal from an aircraft, the first signal including an address corresponding to aircraft identification; means, coupled to the plurality of sensors, for generating a time stamp indicating when the first signal is received at each of the plurality of sensors; means for correcting pseudorange values with atmospheric conditions, including; means for obtaining an initial multilateration solution from time stamp data to calculate initial raw multilateration solutions without regards to atmospheric conditions, means for estimating initial time stamp correction factors based on the knowledge of atmospheric profile between each sensor and apparent target locations, means for adding initial time stamp correction factors to the time stamp data, and deriving nonlinear equation relating true target height with apparent target height at a given range, wherein the nonlinear equation is solved using the apparent target location as input, for what would be true height and range as seen by each sensor. - View Dependent Claims (36, 37)
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38. A 3-D multilateration target tracking system comprising:
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a plurality of sensors for receiving a first signal from an aircraft, the first signal including an address corresponding to aircraft identification; means, coupled to the plurality of sensors, for generating a time stamp indicating when the first signal is received at each of the plurality of sensors; means for improving height determination for regions of poor Vertical Dilution Of Precision (VDOP) in a 3D multilateration system; and a height determination algorithm for obtaining better vertical accuracy in places with good Horizontal Dilution Of Precision (HDOP), the algorithm comprising a 2D tracking system, utilizing altitude information contained in Mode C and Mode S messages to perform reliable 2D tracking of horizontal positions, wherein for any given time, a modified set of 3D multilateration equations is formed by setting the x-y position of the target with that given by the 2D tracking system, obtaining a solution of the unknown altitude by a least-squares technique.
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39. A direct multilateration target tracking system comprising:
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a plurality of sensors for receiving signals from an aircraft; means, coupled to the plurality of sensors, for generating time stamp data indicating when the signals are received at each of the plurality of sensors; means for generating aircraft position x-y position data and velocity by multilaterating the time stamp data; and means for selecting at least one of a best receiver combination and solution of multilateration equations from a multitude of combinations and solutions. - View Dependent Claims (40, 41, 42, 43)
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Specification