The present invention relates to targeting and navigation systems and, more particularly, to triangulation-type targeting and navigating.
U.S. soldiers under mortar or missile attack do not have an effective method of determining the origin of the attack. Usually, it is too late by the time the source of the attack has been located.
It would be desirable to be able to track incoming ordnance, e.g., missiles and mortar, and reverse interpolate where these ordinance originated. Presently, radar cannot track small objects like these.
It is also desirable to be able to determine the destination of airborne objects in real time as well as enabling automated navigation for vehicles, planes and robotic vehicles.
Presently, there are no known systems designed to track and reverse interpolate the origin of incoming ordinance. U.S. Pat. No. 3,937,951 uses two sensors to determine the location of a lightning event. This device is only capable of determining the average location of the lightning event.
If this device were to be used for tracking incoming ordinance, it would not have the accuracy and resolution required to be able to pinpoint the ordinance trajectory.
It is therefore desirable to store real-time trajectory data to be used to predict target destination and calculate target origin.
It is also desirable to measure the exact location of stationary objects for navigation and surveying.
Disclosed herein is a measurement system with at least 2 sensors to identify precise locations of remote objects. The sensors detect electro-magnetic radiation which is either emitted from or reflected off of the object, and measures the elevation and azimuth angles to the target. Given a known distance between the 2 sensors, the system is then able to calculate the exact location of the object using a modified type of triangulation. In the case of moving targets, this data is used to determine target trajectory, origin and destination. In the case of stationary targets, the data is used to determine the exact location of the target for mapping and for navigation to or around the stationary target.
In particular, disclosed herein is a sensor system for tracking and navigation, comprising: two sensors, each sensor comprising a two-dimensional plurality of discrete detection pixels; for each sensor, computerized data associating each detection pixel thereof with a predetermined azimuth angle and a predetermined elevation angle; computerized means for automatically determining azimuth angles and elevation angles of a target or beacon simultaneously detected by each of the sensors, for each of the sensors, based on the computerized data; and computerized means for calculating a three-dimensional position of the target or beacon, based on the azimuth angles and the elevation angles of the target or beacon for each of the sensors, and based on a known distance and relative orientation between each of the sensors.
Further disclosed is a computerized device and related method for use in connection with a sensor system for tracking and navigation, comprising computerized input, storage and processing means for: receiving input data specifying a detection pixel of a sensor which has detected a target or beacon; storing computerized data associating each detection pixel with a predetermined azimuth angle and a predetermined elevation angle; and determining an azimuth angle and an elevation angle of the detected target or beacon from the input data in association with the stored computerized data.
Further disclosed is a method and related apparatus for calibrating a sensor for tracking and navigation, comprising the steps of: striking the sensor with calibration electromagnetic radiation originating at known azimuth and elevation angles; determining which detection pixels of the sensor are activated by the calibration electromagnetic radiation; and associating the activated detection pixels with the known azimuth and elevation angles.
Further disclosed is a sensor system and related method for tracking and navigation, comprising: a sensor comprising a two-dimensional plurality of discrete detection pixels; and computerized data associating each the detection pixel with a predetermined azimuth angle and a predetermined elevation angle; wherein: when a target or beacon is detected by a given pixel of the sensor, an azimuth angle and an elevation angle of the target or beacon is automatically determined from the computerized data.
The features of the invention believed to be novel are set forth in the appended claims. The invention, however, together with further objects and advantages thereof, may best be understood by reference to the following description taken in conjunction with the accompanying drawing(s) in which:
For purposes of clarity and brevity, like elements and components bear the same designations and numbering throughout the FIGURES.
Once the distance and relative orientation between each of the sensors is known, the sensors 10 and 12 (for a two-sensor system) are used to detect electromagnetic radiation from a moving target or beacon 14 located in the sky or on the ground. For use at night, one may employ infra-red or ultraviolet sensors. As will be elaborated in detail below, each sensor in the system is able to independently determine the azimuth angle and the elevation angle to the target or beacon 14. Given the initial conditions of azimuth angles A1, A2, elevation angles E1, E2, and Distance “D” 40 the system processor is able to calculate the exact location of the target using the following trigonometric calculations with right sensor 12 defined as the system origin.
Using
Tan A1=Y/(D+X) (1)
Tan A2=Y/X (2)
In the equation (2) above, solving for X yields:
X=Y/Tan A2 (3)
Substituting equation (3) into equation (1) yields:
Tan A1=Y/(D+(Y/Tan A2)) (4)
Solving for Y in equation (4) yields:
Y=(Tan A1*D)/(1−(Tan A1/Tan A2)) (5)
Next, solving equation (2) for Y yields:
Y=X*Tan A2 (6)
Substituting equation (6) into equation (1) by replacing Y yields:
Tan A1=(X*Tan A2)/(D±X) (7)
Solving equation (7) for X yields the equation:
X=(Tan A1*D)/(Tan A2−Tan A1) (8)
Next, calculating D252 using the Pythagorean theorem yields:
D22=X2+Y2 (9)
and the square root each side yields:
D2=Sqrt(X2+Y2) (10)
This configuration yields the equation:
Tan E2=Z/D2 (11)
Solving for Height “Z” 54 yields:
Z=Tan E2/D2 (12)
Once these X-Y-Z coordinates have been obtained from equations (5), (8) and (12), this process can be reiterated as often as necessary until the target exits the sensors' view, thus providing the basis as well for velocity and trajectory calculations. The data may be represented in the X-Y-Z location coordinates derived above, or in any other suitable coordinate system. The data may also be converted into GPS data if system was initially calibrated with GPS. The trajectory data points obtained can be utilized in a number of ways.
These coordinates may be used directly for surveying. For example, this system could be used to measure distance to the top of a mountain or building if, for example, one points a laser on the mountain or building, and then detects the X-Y-Z coordinate of the laser point.
A series of coordinates with time separation data may be input to a computerized device with suitable hardware, software and storage for calculating a “best fit” trajectory in order to reverse-interpolate the origin of the target. Similarly, series of coordinates with time separation data may be input to a computerized device with suitable hardware, software and storage for calculating a “best fit” trajectory in order to forward-interpolate the destination of the target. That is, it is possible to calculate an origin and/or destination of the target based on the above calculation of three-dimensional position at at least two distinct times.
If left sensor 10 and right sensor 12 are attached to a mobile vehicle and the target or beacon 14 is stationary, the data can be used for navigation.
If both target and vehicle sensors are moving, data can be processed to determine continuous relative position between target and vehicle.
In this way, the foundation for the calculation set forth above is laid by the fact that each sensor comprises a two-dimensional plurality of discrete detection pixels; and by providing computerized data associating each said detection pixel with a predetermined azimuth angle and a predetermined elevation angle; wherein: when a target or beacon is detected by a given pixel of said sensor, an azimuth angle and an elevation angle of said target or beacon is automatically determined from said computerized data.
Referring now to
Someone of ordinary skill may, however, choose from a broad range of storage configurations, all within the scope of this disclosure and its associated claims. The key is that there be computerized data associating each detection pixel with a predetermined azimuth angle and a predetermined elevation angle, irrespective of the particular scheme that is chosen for storing this data.
Repeatable assembly of the sensors is also important. It can be concluded from
One technique for calibrating the system—for example, not limitation—is to place the sensor in a dark room with a reflective ceiling. A laser light can be shined on the ceiling at a known angle of elevation and azimuth. The memory-mapped location for the excited pixel is then assigned the known angles of azimuth and elevation loaded there. A series of reference points are mapped in this manner. All of the data in between the reference points is interpolated from the reference points. This database only needs to be established one time and once acquired it can be reused for all equivalent assemblies. The data base is stored in a lookup table in the system processor.
More generally, sensor calibration comprises the steps of: striking the sensor or an equivalent sensor with calibration electromagnetic radiation originating at known azimuth and elevation angles; determining which detection pixels of the sensor are activated by the calibration electromagnetic radiation; and associating the activated detection pixels with the known azimuth and elevation angles.
Referring now to
Once in the field, the two sensors are aligned by setting a distance between the lasers. For most practical situations, it is desirable to separate the sensors by at least 50 feet for the system to be able to track properly. If the sensors are too close together, there will not be a measurable difference between the active pixels on each sensor. The two sensor are positioned at a height above any moving objects that might enter into the active view filed of the sensors, and leveled with, e.g., a bubble level. Fifteen feet should be sufficient in a typical military camp, though it is recognized that this height may vary depending on situation. Left sensor 10 is rotated such that Laser A 42 hits center mass of right sensor 12. Left sensor 10 also pulses Laser A 42 and measures the time of the reflection for accurate distance measurement. Right sensor 12 is rotated such that Laser B 44 hits center mass of left sensor 10. Now the sensors are ready to measure targets. This establishes a known distance between the sensors.
Referring now to
A simpler variation of the system might employ, for example, 3 sensors in a triangle. In this formation, all three sensors would track data. Only data from the two closest sensors are be used to calculate target position. The two closest sensors are the two with the largest elevation angles.
More generally, such a system comprises at least one additional sensor substantially equivalent to each of the sensors in a two-sensor configuration and comprising substantially equivalent computerized data therefor; and computerized means for calculating the three-dimensional position of the target or beacon, based on azimuth angles and elevation angles of said target or beacon for a selected pair of sensors, and based on a known distance and relative orientation between the selected pair of sensors.
Referring now to
If multiple targets enter the sensory area, each target is given its own identification. This identification is associated with the target's trajectory data in order to differentiate its data for coordinate calculation. Multiple targets are not an issue if this system is used for navigation. While mounted on a vehicle, the system will only track a stationary homing beacon for navigation. If used in conjunction with optical edge recognition type software, this program will identify the exact location of the edges of objects in the vehicle's path and allow for easier auto-navigation.
It is also noted that the data from this system can be converted into polar or GPS coordinates if desired.
While only certain preferred features of the invention have been illustrated and described, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.
This application claims benefit of pending U.S. provisional application 60/522,068 filed Aug. 10, 2004.
Number | Name | Date | Kind |
---|---|---|---|
4516851 | Parker et al. | May 1985 | A |
4622458 | Boech et al. | Nov 1986 | A |
4671650 | Hirzel et al. | Jun 1987 | A |
4780719 | Frei et al. | Oct 1988 | A |
4834531 | Ward | May 1989 | A |
4957369 | Antonsson | Sep 1990 | A |
5198607 | Livingston et al. | Mar 1993 | A |
5351056 | Sawyer | Sep 1994 | A |
5386370 | Woo | Jan 1995 | A |
5586063 | Hardin et al. | Dec 1996 | A |
5631654 | Karr | May 1997 | A |
5642299 | Hardin et al. | Jun 1997 | A |
5812247 | Meyer | Sep 1998 | A |
6043867 | Saban | Mar 2000 | A |
6498580 | Bradford | Dec 2002 | B1 |
6527222 | Redano | Mar 2003 | B1 |
6666401 | Mardirossian | Dec 2003 | B1 |
6675121 | Hardin et al. | Jan 2004 | B1 |
6873406 | Hines et al. | Mar 2005 | B1 |
Number | Date | Country | |
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20070002304 A1 | Jan 2007 | US |
Number | Date | Country | |
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60522068 | Aug 2004 | US |