An airborne reconnaissance system comprising: (1) Gimbals having at least two degrees of freedom; (2) At least one array of light sensors positioned on the gimbals, for being directed by the same within at least two degrees of freedom; (3) Map storage means for storing at least one Digital Elevation Map of an area of interest, divided into portions; (4) Inertial Navigation System for real-time providing to a gimbals control unit navigation and orientation data of the aircraft with respect to a predefined global axes system;(5) Portion selection unit for selecting, one at a time, another area portion from the area of interest; and (6) servo means for directing the gimbals. The system uses data from the inertial navigation system and from the digital elevation map for real-time calculating direction to selected area portions, and for maintaining the direction during integration of light from the terrain, and for producing corresponding images of area portions.

Airborne reconnaissance system

A control system stabilizes a turret having a gimbal and base and pointing a weapon mounted within the turret. The control system includes computer executable modules to receive turret data and operator commands and to modify operator commands in accordance with a generated line of sight vector and ballistic data. The modules include a time optimal controller to generate modified operator commands. The modules further include a gimbal stabilization controller to generate motor commands to stabilize the turret and point the weapon.

Control system for a weapon mount

We propose an on-board selection scheme for aerial and space images, based on linear feature detection in a feature hyperspace. The detection task is performed by means of the Radon transform (RT) and the wavelet transform; a fast algorithm for the RT computation is described, and counteractions against the discretization errors are proposed. A new, wavelet-based algorithm is introduced, which performs a fine analysis of the waveforms of the RT peaks, yielding a possibly error-free detection in images corrupted by a high level of noise. A technique, based on the feature hyperspace, is proposed, able to significantly exploit all the available pieces of information on these peaks. Results of the tests on synthetic and real images are reported, which show that this method achieves satisfactory results, making the detection task highly reliable in the presence of both noise and clutter.

On-board selection of relevant images: an application to linear feature recognition

To obtain the geographical position of the ground target accurately, a geolocation algorithm based on the digital elevation model (DEM) is developed for an airborne wide-area reconnaissance system. According to the platform position and attitude information measured by the airborne position and orientation system and the gimbal angles information from the encoder, the line-of-sight pointing vector in the Earth-centered Earth-fixed coordinate frame is solved by the homogeneous coordinate transformation. The target longitude and latitude can be solved with the elliptical Earth model and the global DEM. The influences of the systematic error and measurement error on ground target geolocation calculation accuracy are analyzed by the Monte Carlo method. The simulation results show that this algorithm can improve the geolocation accuracy of ground target in rough terrain area obviously. The geolocation accuracy of moving ground target can be improved by moving average filtering (MAF). The validity of the geolocation algorithm is verified by the flight test in which the plane flies at a geodetic height of 15,000 m and the outer gimbal angle is <47°. The geolocation root mean square error of the target trajectory is <45 and <7  m after MAF.

Ground target geolocation based on digital elevation model for airborne wide-area reconnaissance system

A method and apparatus for use with a satellite positioning system wherein the receive elements satellite positioning system receive antennas are maintained in an orientation with respect to the positioning system satellites in a way such that the strongest signals can be received from the greatest number of satellites. According to one embodiment, a housing of a positioning antenna is mounted in a gimbaled fashion onto a vehicle, such as an excavator. Such a gimbaled antenna maintains a horizontal orientation relative to a predetermined axis and, as a result, remains in a position to receive signals from positioning system satellites even during instances of high angular deflection of the antenna support, such as may occur during earth-moving operations.

Gimbaled satellite positioning system antenna

TIER II Plus is a high altitude unmanned reconnaissance aircraft carrying a synthetic aperture radar (SAR) and electro-optical/infrared (EOIR) sensor that will provide all-weather, day and night, high resolution imagery of ground targets for joint armed forces users. Its high area coverage rate is achieved in near real-time by transmitting the collected imagery while the vehicle is airborne and relaying that imagery via satellite to ground stations for processing and dissemination. The electro-optical sensor assembly consists of a mid-wave infra-red (MWIR) staring array built by Hughes Aircraft Company and a CCD visible staring array from Kodak that share common reflective optics. The telescope/sensor subassembly is mounted on the inner gimbal of a two axis gimbal set that directs the sensor line-of-sight (LOS) to designated earth-fixed locations. An on-gimbal inertial rate sensor provides the 2-degree-of-freedom (2DOF) inertial reference to stabilize the sensor LOS. An off-gimbal GPS-aided inertial navigation system (INS) provides aircraft navigation data to the control system for inertial position stabilization and for determining the target image geolocation. Fine stabilization and step/stare requirement is jointly achieved with two-axis image motion compensation (IMC) mirror mechanisms mounted internally in the telescope optical train. This paper describes the salient features of the TIER II Plus control system design with emphasis on the algorithms used for LOS control, command generation, and target image geolocation. Computer simulation results will be presented to support the design.

B.H. Robinson

Papers

TIER II Plus airborne EO sensor LOS control and image geolocation