# US 2013/0153707 A1 · Guidance method and apparatus

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- Number: US 2013/0153707 A1
- Document ID: US20130153707A1
- Status: Published application
- Kind: A1
- Application number: 13/254,738
- Filed: 2011-08-23
- Published: 2013-06-20
- Earliest claimed: 2010-08-23
- Assignees: Mbda UK Limited
- Inventors: Martin Simon Gate
- Web page: https://patentgrep.com/patent/US20130153707A1

## CPC

- F41G 9/00: Systems for controlling missiles or projectiles, not provided for elsewhere
- F41G 7/22: Homing guidance systems
- F41G 7/30: Command link guidance systems {(homing F41G7/2206)}
- G05D 1/12: Target-seeking control
- F41G: WEAPON SIGHTS; AIMING (optical aspects thereof G02B)
- G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES

## Abstract

A method of guiding a pursuer to a target is provided, and is of particular use when the possible target location is described by non-Gaussian statistics. Importantly, the method takes into account the fact that different potential target tracks in the future have significantly different times to go. That can give rise to emergent behaviour, in which the guidance method covers several possible outcomes at the same time in an optimal way. An example embodiment of the method combines Particle Filter ideas with Swarm Optimization techniques to form a method for generating guidance commands for systems with non-Gaussian statistics. That example method is then applied to a dynamic mission planning example, to guide an airborne pursuer to aground target travelling on a network of roads where the pursuer has no-go areas, to avoid collateral damage.

## Claims

### Claim 1

A method of guiding a pursuer to a target, the method comprising:
(a) providing a plurality of possible target trajectories, weighted to represent a probability distribution of the target trajectories;
(b) providing a plurality of candidate guidance controls, parameterised by a candidate guidance parameter;
(c) for each of a plurality of values of the candidate guidance parameter:
a. determining a projected pursuer trajectory resulting from the candidate guidance control corresponding to the candidate guidance parameter value;
b. using the projected pursuer trajectory so far developed, determining the next occurrence of a termination condition for the pursuer trajectory relative to any of the target trajectories for which a termination condition has not yet occurred;
c. adjusting the projected pursuer trajectory, subsequent to that termination-condition occurrence, to account for that target trajectory;
d. repeating steps b and c until the termination conditions corresponding to all of the plurality of possible target trajectories have been accounted for; and
e. recording a cost for the candidate guidance control based on the projected pursuer trajectory and the miss distances at the termination-condition occurrence for each target trajectory;
(d) generating a revised plurality of values of the candidate guidance parameter in view of the recorded costs of the candidate guidance controls;
(e) repeating steps (c) and (d) a plurality of times and identifying an optimal guidance control based on the recorded costs;
(f) applying the optimal guidance control to the pursuer to alter its actual trajectory;
(g) obtaining updated possible target trajectories; and
(h) repeating steps (b) to (g) a plurality of times.

### Claim 2 (depends on 1)

A method as claimed in claim 1, in which the termination condition relative to a target trajectory is the point of nearest approach of the projected pursuer trajectory to the target trajectory.

### Claim 3 (depends on 1)

A method as claimed in claim 1, in which the candidate guidance parameter is a costate parameter.

### Claim 4 (depends on 1)

A method as claimed in claim 1, in which the target trajectories are described by non-Gaussian statistics.

### Claim 5 (depends on 4)

A method as claimed in claim 4, in which the target trajectories are possible routes of a target vehicle.

### Claim 6 (depends on 1)

A method as claimed in claim 1, in which the revised plurality of values of the candidate guidance parameter are generated using an optimisation algorithm.

### Claim 7 (depends on 1)

A method as claimed in claim 1, in which the optimisation algorithm is a swarm algorithm.

### Claim 8 (depends on 7)

A method as claimed in claim 7, in which the swarm algorithm is a master-slave swarm algorithm.

### Claim 9 (depends on 1)

A method as claimed in claim 1, comprises uncurling a projected trajectory by damping a high-frequency oscillation in the projected trajectory.

### Claim 10

(canceled)

### Claim 11

(canceled)

### Claim 12

(canceled)

### Claim 13

(canceled)

### Claim 14 (depends on 1)

Processing apparatus arranged to carry out the steps of a method as claimed in claim 1.

### Claim 15 (depends on 14)

A vehicle comprising processing apparatus as claimed in claim 14.