Abstract: A method for searching a radar acquisition volume after rotating the radar acquisition volume is disclosed. The method may comprise identifying an acquisition face of the acquisition volume and partitioning the acquisition face so that each partitioned portion of the acquisition face can be searched within a predetermined time period. The partitioning step may comprise determining the maximum number of beams that can be searched in a predetermined period of time and iteratively repositioning an elevation line on the acquisition face to identify the highest elevation line for which the number of radar beams is less than or equal to the maximum number of beams. The partitioning step may also comprise defining a beam lattice for the acquisition face and determining a maximum elevation line based on the beam lattice. The area of the acquisition face bounded by the highest or maximum elevation line defines the partitioned portion.

Abstract: A method and radar system for estimating a radar search volume, includes acquiring covariance information relating to a cued direction, the covariance information having an ellipsoidal shape, projecting the ellipsoidal shape covariance information onto a range-traverse plane and onto the range-elevation plane to produce a covariance ellipse on the range-traverse and range-elevation planes; and determining the maximum extents in each of the range-transverse and range-elevation planes wherein the azimuth and elevation extents define the search volume.

Abstract: A target in a mobile platform's obstructed zone can be cleared from the obstructed zone and engaged in the most time-efficient manner by determining the direction of the maneuver that would require the shortest amount of time to clear the target and then maneuvering the mobile platform in that direction.

Abstract: A radar volume in a cued direction is searched with sequential pencil beams. The cued direction is subject to uncertainty in the form of covariance. The covariance defines an ellipse rotated relative to the azimuth axis. Before determining the extent of the acquisition face, the ellipse is projected onto a viewplane normal to the radar range axis, and rotated so the principal axes are parallel with the traverse and elevation directions. The acquisition face is then found. The number of beams required to scan the search volume is determined. In one embodiment, the search volume is sent to the radar, and the radar rotates the beams to their correct positions. The beams are then scheduled.

Abstract: A method according to an aspect of the disclosure is for partitioning a radar acquisition volume, the method comprising the steps of: determining an allocated time to search an unpartitioned volume; determining a number of beam rows in an unpartitioned acquisition face; determining an average per-row search time for searching the angular region based on the determined allocated time and determined number of beam rows in an unpartitioned acquisition face; determining a number of beam rows in an allotted acquisition period that is searchable based on the average per-row search time; calculating a maximum elevation extent based on the number of beam rows in the allotted acquisition period; and searching an angular extent of the search volume based on the calculated maximum extent.

Abstract: Radar beams for searching a volume are selected by determining the central angle and azimuth and elevation extents to define an acquisition face. The number of beams NMBA required to cover the acquisition face is determined by N MBA = ( 2 ? n + 1 ) ? ( m + 1 2 ) + ( - 1 ) n + m 2 ( 2 ) The number of beams NMBA is multiplied by the dwell per beam to determine the total search time, which is compared with a maximum time; (a) if the total search time is greater than the permissible time, the acquisition face is partitioned, and (b) if the total search time is less, the acquisition face information is applied to a radar processor for filling the unextended acquisition face with the number NMBA of beams in a particular pattern.

Abstract: A maximum gap method and system provide for identifying a space sector within which a system capable of engaging an object, should search for the object. A detector system that may be a radar or other active range determination system tracks position of the moving object and based on position estimates and the uncertainties associated with the position estimates, generates a range of possible positions for each estimate then determines gaps between the uncertainties and derives the search sector based on the maximum gap.

Abstract: A radar volume in a cued direction is searched with sequential pencil beams. The allowable scan time is limited. The cued direction and uncertainty identify a search face, and the range gives a search volume. The number of beams required to scan the volume is determined, and compared with the maximum time. If less than the maximum, the scan is initiated. If greater than the maximum time, the scan region about the cued volume is subdivided into smaller portions, each of which is scanned sequentially.

Abstract: A plurality of targets in a mobile platform's obstructed zone can be cleared from the obstructed zone and engaged in the most time-efficient manner by maneuvering the platform to clear and engage each target having the minimum clearance displacement in turn as measured from the platform's position following each maneuver.

Abstract: A sensor includes transducer(s) for observing a region, and produces raw data representing the observed object. The raw data is processed to produce evidence signals representing one or more characteristics of the object. Taxonomic (type) classification is performed by a method using N Bernoulli trials.

Abstract: A plurality of sensors observe an object, and the raw sensor data is processed to produce evidence signals representative of characteristics which may be used to classify the object as to type. The sensor response characteristics from the plurality of sensors are fused to generate fused or combined sensor response characteristics. Thus, the fused or combined sensor response characteristics are equivalent to the sensor response characteristics of a virtual sensor. The evidence and fused sensor response characteristics are applied to a taxonomic classifier to determine the object type.

Abstract: An active or passive sensor observes a region, and generates evidence of the type of target or object viewed. The evidence is processed to determine the prior probability that the object is of a particular type. The prior probability so determined is thresholded to produce an indication of the presence of multiple targets or objects in a range bin, suggestive of shadowing of a target.

Abstract: A plurality of sensors observe an object, and the raw sensor data is processed to produce evidence signals representative of characteristics which may be used to classify the object as to type. The evidence from the plurality of sensors is fused to generate fused or combined evidence. Thus, the fused evidence is equivalent to signals produced by a virtual sensor. The fused evidence is applied to a taxonomic classifier to determine the object type.