Publication number | USRE42546 E1 |
Publication type | Grant |
Application number | US 11/318,398 |
Publication date | Jul 12, 2011 |
Filing date | Dec 22, 2005 |
Priority date | Mar 27, 2002 |
Fee status | Paid |
Also published as | US6668218 |
Publication number | 11318398, 318398, US RE42546 E1, US RE42546E1, US-E1-RE42546, USRE42546 E1, USRE42546E1 |
Inventors | Jeffrey Bulow, Douglas M. Peters |
Original Assignee | Nevada Asset Liquidators, Llc |
Export Citation | BiBTeX, EndNote, RefMan |
Patent Citations (32), Non-Patent Citations (6), Referenced by (4), Classifications (19), Legal Events (3) | |
External Links: USPTO, USPTO Assignment, Espacenet | |
The present inventions relate to localization of an object or target of interest.
It is often desirable to track one object from another object to determine if the tracked object will intercept the tracking object, or at what point in time will the tracked object be at it closest approach to the tracking object, sometimes referred to in the art as “Target Motion Analysis.” For example, a vessel afloat in the presence of subsea or partially submerged obstacles would need to know where those obstacles are in order to avoid hitting those obstacles. By way of example and not limitation, such systems have been proposed in the art to avoid collisions with other vessels, collisions with such as icebergs, and collisions with submerged objects sufficient to cause damage such as ledges, seamounts, or reefs.
Some of the prior art has proposed using statistically based tracking methods. For example, U.S. Pat. No. 5,732,043 to Nguyen et al. for “Optimized Deterministic Bearings Only Target Motion Analysis Technique” teaches using four target bearings to optimize a target track solution.
In other art, U.S. Pat. No. 6,199,471 issued to Perruzzi, et al. for a “Method And System For Determining The Probable Location Of A Contact” teaches a method and a system for determining a weapon firing strategy for an evading target. Perruzzi '471 comprises the steps of sensing the motion of the target, analyzing the motion of the target, providing a weapon employment decision aid, determining the evasion region for the target using the weapon employment decision aid and the analyzed motion, visually displaying the evasion region, feeding operator knowledge about evading target, and generating a representation of the probability of the location of the evading target.
U.S. Pat. No. 5,867,256 to Van Rheeden for “Passive Range Estimation Using Image Size Measurements” teaches a range estimation system and method which comprises a data base containing data for identification of certain targets and data for estimating the initial range to each of the targets as a function of the observed dimensions of the targets. A sensor (1) observes a scene containing a target a plurality of spaced apart times while the sensor is moving relative to the target to provide data from each observation of the scene relating to the dimensions of the target within the scene. The remaining range to the target is estimated from the observed dimensions of the target from the range traveled since a prior estimation of range and from a prior estimation of the remaining range to the target. The sensor (1) provides electrical signals representing the observed scene (3) and can be a visible light or infrared sensor. A computer (9) is used to identify the target from the data base, estimate the initial range to the target and estimate the remaining range from the range traveled between successive observations of the scene and the change of dimensions of the target in the observed scene.
As noted in the prior art, there are a number of situations where it is desirable to estimate the range to an object of interest or target (e.g. aircraft without the aid of instrument landing systems, automobiles that would be aware of the distance between vehicles to avoid collisions, and missile-based warfare). As also known in the art, active techniques to measure range, such as radar, ladar and sonar, have drawbacks, primarily in military applications, including easy detection by the target under attack. This is true, for example, in submarine warfare where one vessel may want to use sonar to determine the position and velocity of an enemy ship. In such situations, it is advantageous to estimate range to the target passively.
For passive tracking situations, in order to react quickly, tracking methods would preferably fix a boundary on the range to the tracked object quickly while using a minimum amount of data, preferably passive data. Further, it is preferable to calculate the bearing of the tracked object with respect to the tracking object at a point of closest approach, along with calculating a time to that closest approach, independent of other position data.
The AN/SQQ-89(V) UFCS (Navy) surface ship ASW Fire Control System currently uses the Manual Adaptive Target Estimator (MATE) and Maximum Likelihood Estimator (MLE) algorithms to determine target position. These algorithms require substantially more data than the present inventions to obtain their results. The MATE algorithm requires operator based estimates, and systematic manual manipulation of the data to arrive at a position, course and speed estimate of the target. The MLE algorithm also requires limited operator input to arrive at a statistically based estimate of position, course and speed of the target. Both of these algorithms require a substantial amount of data, approximately fifteen to twenty data points, to arrive at a stable solution.
These and other features, aspects, and advantages of the present inventions will become more fully apparent from the following description, appended claims, and accompanying drawings in which:
Referring to
In a preferred embodiment, the methods of the present inventions may be used to conduct passive TMA using symmetries associated with two different views of a problem to be solved, e.g. two reference frames and two points of interest. A first of these frames, geographic frame of reference 100, is shown in
As used herein, the “points of interest” include a first physical object such as ownship 1, and a second, target 2, such as second vessel. As further used herein, “ownship” means a first reference point that is not a target, i.e. the vessel making the calculations. Each of these points of interest may be in motion or stationary, and, if in motion, may be in motion in different planes with respect to each other. “Target motion analysis” or TMA means that the course and speed for target 2, which may initially be unknown, are resolved as well as the range to and bearing of target 2 at or for a predetermined time frame with respect to ownship 1. In a preferred embodiment of the present inventions, bearing at CPA, time of CPA, a minimum range to the target with associated course and speed for the minimum range only as a limiting condition, and an initial estimate of the target's true range, course and speed may be determined.
The methods of the present inventions are not limited to surface or subsea water vessels. By way of example and not limitation, target 2 may be another vessel, an iceberg, a submerged object such as a ledge or reef, or the like, assuming that target 2 emits a signal that can be detected by a passive sensor for the passive solution. Further, the methods of the present inventions may be used with partially or fully submerged features such as rocks or debris, floating materials, stationary materials, and the like, or combinations thereof, especially if the presence of such features may be determined, but a measurement of range to the feature may be lacking in the detection device that detects the feature. However, it is expressly understood that active as well as passive data may be used in the present inventions' methods, in which case any single active signal may be used to determine a range value which can then be used in conjunction with passive data to fully resolve range, bearing, course and speed.
In general, the present inventions' methods comprise obtaining at least three bearing and time data points for a first estimate, e.g. at time points t_{1}, t_{2}, t_{3}, t_{4}. These data are used to isolate a passive TMA estimate based on a single leg of time tagged, bearings only data, i.e. no maneuvering of the first point of interest such as ownship 1 is required to obtain a passive estimate. Further, the present inventions' methods comprise a closed form expression for an estimate that may be resolved in a single iteration as opposed to prior art methods such as those using first order statistical solutions.
The present inventions' methods utilize velocity vectors of the two items of interest, i.e. vector 13 and estimated vector 30. These velocity vectors, when arranged to determine their vector difference, form one side 52, 53 of a parallelogram as well as a diagonal of that parallelogram, shown as darkened portion 51 of vector 13. For the parallelogram to remain a parallelogram when angles of vertices of the parallelogram change, the perpendicular distances to respective opposite sides of the parallelogram change in a predetermined fashion, i.e. as the angles of the parallelogram whose diagonal remains at substantially the same orientation to ownship 1's constant course, change from π/2, the corresponding length of the diagonal must increase by an amount equal to the relative velocity of ownship 1 and target 2 multiplied by the new elapsed time value for the second course crossing minus t_{0}, such that perpendicular distance to opposing sides increases by an amount proportional to twice the range at CPA. Additionally, the greater the difference between values of adjacent vertices, the smaller the perpendicular distance to opposing sides.
Further, successive time-lagged bearing lines, e.g. lines 11 and 12, form a parabola, shown as solution parabola 15, in geometric reference frame 100 for substantially all geometries involving two points of interest 1,2, where each of the points of interest 1,2 maintains a substantially constant respective course and speed over a time period used for obtaining bearing measurements. Solution parabola 15 is formed by recognizing that each of the bearing lines 11,12,13,20,30 in geographic reference frame 100 are tangent to solution parabola 15 at a predetermined, unique point. If the bearing lines of a data set belonging to one target are tangent to solution parabola 15 at various points along solution parabola 15, and if the angles of the parallelogram vertices change such that the angle of course incidence deviates from the value at which the relative velocity vector bisects the angle of course incidence and the courses represented by two of the parallelogram sides are constrained to remain tangent to the parallelogram, the perpendicular distance to opposing sides always increases. This increase may only be accomplished by increasing the parallelogram perimeter.
Accordingly, solution parabola 15 will be fixed in geographic reference frame 100, and each data set to be gathered will generate one and one only solution parabola 15, although different data sets may generate the same solution parabola 15. Further, for all potential pairs of bearing lines 11,12,13,20,30 tangent to solution parabola 15 when the course of ownship 1 is one of the bearing lines and remains fixed, e.g. line 13, the value of the bearing at the CPA, e.g. angle 50′, is constant for potential ranges at CPA. As a result, the difference vector of each potential velocity vector pair, i.e. velocity vector for target 2 and velocity vector of ownship 1, remains parallel for all geometries involving those two points of interest where each point of interest 1, 2 maintains its respective course and speed at a constant value during the time of measurements and calculation. This allows calculation of bearing at CPA, time of CPA, and minimum range at CPA, with data comprising a single leg of passive, time tagged bearings. Further, this allows estimates of TMA solutions based on minimum range and preferred range estimates with data comprising a single leg of passive, time tagged bearings.
Referring now to
In the case where the incident angle of the mutual courses of target 2 and ownship 1 is greater than π/2, an additional step may be required to reflect the original bearing line data, e.g. 13, around a preferred bearing line in the original data set indicated by the axis of original solution parabola 15 to generate revised parabola 15 for a set of pseudo-data that reflects the course of target 2 in a reference frame for which the incident angles of courses is less than π/2. This situation will also require extrapolating the course of ownship 1 into a predetermined future time point and reversing the course such that the ownship arrives at the same point at the time ownship 1 crosses the course of target 2.
Referring additionally to
Bearing data may then be translated to a moving ownship reference frame 200. Two sets of data may form vectors, one set representing target 2, e.g. 30, and the other set representing ownship 1, e.g. 13, which may then cross each other at different times. By way of example and not limitation, vectors 30 and 13 may cross when target 2 appears at 0° relative bearing or 180° known bearing, or when ownship 1 appears at 0° relative to the course of target 2 or when ownship 1 appears at 180° unknown to the course of target 2.
As will be understood, a large, potentially infinite number of potential solution points may exist based on passive bearing data. Accordingly, the present inventions' method selects at least one potential solution point, e.g. bearing line 20, to indicate a range at CPA. In a preferred embodiment, bearing line 20 may be selected manually by examining target geometry. In alternative embodiments, bearing line 20 may be selected automatically such as by using artificial intelligence methods, heuristics, or the like, or a combination thereof.
Referring back to
tan(θ_{β}−θ_{i})/=V_{REL}(t_{β}−t_{i})/R_{CPA}|θ_{i}=0 (1)
t_{β}=R_{CPA}[tan(θ_{β}−θ_{i})/V_{REL}]+t_{i}|θ_{i}=0 (2)
In these equations (1), (2), and (3),
The formulae of the present inventions' methods may then be used to calculate a bearing fan to determine bearing data at a predetermined time in the future, independent of other position data. A bearing fan is a group of bearing data spaced at predetermined points in time that predicts where in bearing space target 2 will be at some point in future time, assuming that target 2 and ownship 1 maintain their current course and speed. By way of example and not limitation, the present inventions may be used to generate both relative and true bearings and time at CPA, where the time at relative bearing equals zero degrees (0°) or one hundred eighty degrees (180°).
The formulae also provide an early estimate of minimum target ranges for any bearing, independent of other position data. Further, the formulae may be useful in many other ways, by way of example and not limitation for providing parameters useful for early target maneuver detectors or Open/Close determinations as well as estimates of a ratio of relative speed to range at CPA.
The present inventions' methods may further be used to provide a real-time measure of the effect of noise on potential solutions. In a preferred embodiment, this real-time measure begins with a fourth data point, e.g. data point t_{4}.
Having selected a potential solution point, e.g. bearing line 20, the direction of the relative velocity vector 60 can be determined.
Referring now to
Data sets comprising passive bearing data may be gathered such as by using one or more sensors (shown as 230 in
Using the range calculation software, the computer may retrieve at least three of the stored bearing data points obtained from the bearing detector, such as from the computer's memory. The range calculation software may then use the three retrieved bearing data points to determine a speed contribution V_{os }cos(θ_{β}) of a first point of interest to a distance from a relative velocity vector over a time from t_{0 }to t_{0}′ in accordance with the teachings of the present inventions. By way of example and not limitation, in accordance with the teachings of the present inventions the range calculation software may determine an angle θ_{β }defined by the bearing of target 2 relative to a heading of ownship 1 at the point in time of closest approach to a second point of interest and then calculates a minimum range from the source to the target as
Min R_{CPA}=V_{os}(t_{β}−t_{i})cos(θ_{β}−θ_{i})_{θ} _{ i } _{|=0}; and
The range calculation software may then generate a representation of the probability of the location of target 1 and present that information such as on the output device.
In the operation of an exemplary embodiment, referring to
tan(θ_{i}−θ_{0})=(t_{i}−t_{0})(V_{R}/R_{CPA}) (4)
As used in equation (4),
Additionally, it is noted that relative velocity vector 60 is perpendicular to the relative bearing line 20 at CPA in fixed ownship reference frame 100, allowing for calculation of a minimum range estimate at CPA R_{CPA }that is substantially independent of actual contact range. By way of example and not limitation, although at this point the “correct” solution may be unknown, a minimum range estimate calculation is possible because a point when CPA occurs is known as is the point at which target 2 is detected at relative bearing equals θ_{β}. The minimum range estimate for the distance at which ownship 1 is closest to target 2, R_{CPA}, shown in
Min R_{CPA}=V_{os}(t_{β}−t_{0})cos(θ_{β}−θ_{0}) (5)
In equation (5),
If an actual solution is selected, a right triangle may be formed by using ownship vector 51 multiplied by the Δt_{CPA }as the hypotenuse 32 of that triangle. Accordingly, the contact's range at CPA may be determined using hypotenuse 32, the relative bearing at CPA, and the relative velocity vector as follows:
R_{CPA} _{ est }=V_{OS}*Δt_{CC}*cos(θ_{β}) (6)
where
Accordingly, using these estimates, the following calculations can then be made. For bearing BRG at CPA, independent of actual contact range,
In equation (7),
For the ratio of relative speed to the range at CPA,
In equation (8),
For the time of CPA independent of actual contact range,
In equation (9),
For an estimate of the minimum range at CPA, independent of actual contact range,
MinR_{CPA}=V_{os}(t_{β}−t_{i})cos(θ_{β}−θ_{i})_{θ} _{ i } _{|=0} (10)
In equation (10),
Using these formulae, an estimate of minimum range at a predetermined time may therefore calculated by:
Min R_{est}=Min. R_{CPA}/cos(θ_{β}−θ_{j})|θ_{j}=current bearing measure (11)
where the terms in equation (11) are defined above.
Further, from an estimate of R_{CPA(Minimum) }an estimate of the current minimum range at any time t_{i }make be found using the following formula:
R_{(CURRENTMINIMUM)}=R_{CPA(MINIMUM)}/cos(θ_{0}−θ_{i}) (14)
In an exemplary embodiment, the above may be used to base target open-close on measurements calculated at the time of the decision.
Referring now to
Additionally, the estimates may be used to determine noise or a range of noise in the readings. By way of example and not limitation, a set of five or more usable bearing points may be interpreted as a set of calculated points P_{1}, P_{2}, and P_{3 }obtained in accordance with the teachings of the present inventions during times {t_{6},t_{7},t_{8}}, {t_{7},t_{8},t_{9}}, and {t_{8},t_{9},t_{10}} (these time points are not shown in
Referring back to
Prior art methods look at each bearing measurement as a unique point in “the” solution set and do not consider triplet-wise combinations of points as potential solutions to the angle at CPA, each one as valid as the other, if the bearing measurements are independent. Therefore, with the present inventions, with four data points, four potential solutions may be investigated; with five independent points, ten potential solutions may be investigated; and with six independent points, twenty potential solutions may be investigated. This is quickly recognized as the number of possible combinations of n items taken three at a time. A statistical analysis of the potential solutions may then yield trends and/or the mean and standard deviation of bearings at CPA. The mean of the bearing at CPA and the mean time of CPA are more accurate solutions of the bearing at CPA and time of CPA than any one potential solution based on a triplet of bearing measurements.
Thus, the present inventions may allow creating twenty solutions with only six data points rather than waiting for twenty data points. Likewise, four points may be sufficient to determine that there is noise in system and calculating four bearing angle solutions at CPA provides a first order estimate of the magnitude of the noise and a first order estimate of the mean bearing at CPA and mean time of CPA.
It is also noted that in the preferred embodiment, bearing rate curve inflection points are always plus or minus around 30° of the BRG at CPA.
It will be understood that various changes in the details, materials, and arrangements of the parts which have been described and illustrated above in order to explain the nature of this inventions may be made by those skilled in the art without departing from the principle and scope of the inventions as recited in the following claims.
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U.S. Classification | 701/21, 701/98, 701/1, 342/455, 367/99, 340/436, 701/300, 701/301, 180/168, 701/27, 701/36, 701/472 |
International Classification | B60L15/00, G01S19/46, G01S5/18, G01S5/02, G01S19/09 |
Cooperative Classification | G01S3/8086 |
European Classification | G01S3/808C |
Date | Code | Event | Description |
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Aug 3, 2010 | AS | Assignment | Owner name: TECHNOLOGY, PATENTS AND LICENSING III, LLC, PENNSY Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:LOCKHEED MARTIN CORPORATION;REEL/FRAME:024779/0612 Effective date: 20050218 Owner name: NEVADA ASSET LIQUIDATORS, LLC, NEVADA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:TECHNOLOGY, PATENTS & LICENSING III, LLC;REEL/FRAME:024779/0630 Effective date: 20050420 Owner name: LOCKHEED MARTIN CORPORATION, MARYLAND Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:BULOW, JEFFREY ALAN;PETERS, DOUGLAS MARTIN;REEL/FRAME:024779/0582 Effective date: 20020613 |
Nov 22, 2011 | CC | Certificate of correction | |
May 26, 2015 | FPAY | Fee payment | Year of fee payment: 12 |