Aeronautics and astronautics – Missile stabilization or trajectory control – Automatic guidance
Reexamination Certificate
1989-11-22
2001-08-28
Gregory, Bernarr E. (Department: 3662)
Aeronautics and astronautics
Missile stabilization or trajectory control
Automatic guidance
C244S003100, C244S003160, C244S003170, C244S003190, C342S062000, C342S063000, C342S195000
Reexamination Certificate
active
06279851
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to a topography-aided missile guidance system and to a process for incorporating topographical information into missile guidance systems.
2. Description of Related Art
Until now, conventional missile guidance systems used an intercept logic based upon a projected trajectory of the target, commonly implemented with Kalman filters. However, for targets that drop out of sight for extended periods, or for targets that can execute violent maneuvers accompanied by large changes in speed, the prediction uncertainty becomes unacceptably large.
SUMMARY OF THE INVENTION
This invention relates to a topography-aided missile guidance system that minimizes the probability that an airborne target can escape the missile's intercept envelope, where the minimization is over substantially all of the potential actions that the target may take. The system includes means for determining a plurality of feasible paths for airborne targets, means for evaluating the feasible paths and means for selecting a response based upon the probabilities of the targets following the feasible paths.
The means for determining the feasible paths comprises two stages. In the first stage, the system generates a set of paths, called feasible corridors, over a desired area. The feasible corridors define paths from a plurality of points contained within the desired area to one or more predicted destinations. The second stage of the determination occurs each time the target is detected. In the second stage, the system generates a second set of paths, called immediate paths. The immediate paths define paths within a smaller area, that area being centered on the most recently detected target position.
To determine the feasible corridors, in preferred embodiments, the system begins by predicting target intent. Target intent includes a prediction of the target's intended destinations and the general flight tactics of the target, including the target's attempt to avoid detection as much as possible. In preferred embodiments, up to five prospective destinations of the target are selected.
The feasible corridors are defined as the paths from a given point within the desired area to each of the prospective destinations, considering the topographical information relating to the area between those points. In preferred embodiments, a terrain data base is used to provide the topographical information.
In generating the feasible corridors, the system establishes a rectangular grid over the terrain data base. The grid defines path segments connecting various intersections (nodes) of the grid.
In preferred embodiments, the distance between adjacent nodes on the grid is 500 meters. However, other distances between nodes may be chosen in accordance with constraints imposed by the data base, and the desired precision and the processing speed of the system.
By connecting path segments, a path can be generated connecting any given node on the grid to the node nearest the prospective destination. However, since many different paths exist from a given node to the node nearest a given prospective destination, feasible corridors are generated by identifying which of the paths is optimal.
Identifying the optimal paths requires a comparison of the different paths. In comparing the different paths, the system considers various parameters relating to the topography adjacent to the paths. A cost, relating to the various parameters, is assigned to each path segment on the grid. A total cost for a given path can then be calculated by summing the costs of the path segments defining the path.
The costs are assigned according to an equation, or cost function. In preferred embodiments, the cost function is the weighted sum of three parameters: distance to the target, height of the terrain, and masking angle. However, in other embodiments, different cost functions may be used. The cost function generally is comprised of one or more parameters used to assign a cost to a given path segment.
A cost is associated with each path segment, in a direction defined as the direction from one given node to another. Thus, a feasible corridor is generated by identifying the path C, constructed of the path segments connecting a given node to the node nearest to a prospective destination, that minimizes
∫
C
(
α
+
β
z
(
s
)
-
γ
m
(
s
)
)
d
s
,
where z(s) is the terrain height and m(s) is the masking angle over path segment ds.
Masking angle is the angle measured to the horizon, in the direction of the prospective destination, from each node. Thus, the masking angle would be near zero in flat, open areas; the angle would be large for a node located behind a hill; and the angle could be negative for a node positioned on top of a hill.
The parameter weights &agr;, &bgr;, and &ggr; represent the relative importance among the distance, terrain height and masking angle parameters. In preferred embodiments, the various weights are set based upon the predicted intent of the targets. Setting the weights (&agr;, &bgr;, &ggr;) to (1,0,0) will give maximum weight to distance, resulting in a straight line path; a setting of (0,1,0) will give maximum weight to terrain height, resulting in a typical valley following, terrain avoidance path; and a setting of (0,0,1) will give maximum weight to masking angle, yielding a path that maximizes terrain masking over the path.
The weights reflect the relative importance among the three parameters. Therefore, as an example, a setting of (0.5,0.5,0) reflects the equal importance of distance and terrain height, and the relative insignificance of masking angle. The weights in this example will yield a path that deviates from a straight line when a substantial reduction in flight altitude can be obtained.
The feasible corridors are then generated, via the cost function, between each node on the grid and the node closest to each prospective destination. Once generated, the system stores the feasible corridors as fields, one field relating to each prospective destination. Each field consists of a cost matrix, giving the total integrated cost to the prospective destination from each node, and a direction matrix, showing the direction to take from each node along the feasible corridor. Once computed, these matrices need not be recomputed unless a change of prospective destinations or a change of the parameter weights is desired.
With the set of feasible corridors generated, the system utilizes the second stage, or immediate path generator, in determining the feasible paths. The immediate path generator is employed each time the target is detected.
Like the feasible corridor generator, the immediate path generator assigns costs to path segments between two nodes of a grid. However, the immediate path generator utilizes a second grid, centered on the node closest to the most recently detected target position.
In preferred embodiments, the second grid is a rectangle which extends approximately one-third of the distance from the most recently detected target position to the prospective destinations. The second grid, superimposed on the first grid, focuses on alternative paths to the feasible corridors within the immediate area of the most recently detected target position.
The immediate paths are defined as the minimum cost paths between the center node of the second grid (representing the most recently detected target position) and each node on the perimeter of the second grid. Like the feasible corridor generator, a designated cost function is minimized to define the minimum cost paths. The minimum cost paths are stored in a field consisting of a cost matrix, giving the total integrated cost from the center node to each node of the second grid, and a direction matrix, showing the direction to take from each node along the minimum cost path. These matrices are recomputed each time the target is detected.
In preferred embodiments, the path taken by the target, a
Huss Ronald E.
Vitali Robert E.
Alkov Leonard A.
Gregory Bernarr E.
Lenzen, Jr. Glenn H.
Raytheon Company
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