BAE Systems plc

A computer-implemented method of computing training data for training an air data estimator ( 106 ) to predict values of air data parameters ( 120 ) of an aircraft ( 100 ) comprises: selecting ground truth values of the air data parameters ( 120 ) according to a flight envelope of the aircraft ( 100 ). The method involves simulating corresponding values from avionics in the aircraft ( 100 ) by using stored empirical data about engines of the aircraft ( 100 ) and empirical data about the aircraft ( 100 ) obtained from wind tunnel testing, and rules of computational fluid dynamics.

In an aircraft in flight, a feasibility display indicative of a feasibility of a weapon successfully engaging a target and/or a feasibility of a weapon successfully engaging the aircraft is generated The feasibility display may be generated by providing a database describing a performance envelope of the weapon, creating coefficients characteristic of that performance envelope using a generic algorithm, the creating including identifying a best candidate polynomial from a plurality, where variables thereof being some or all of a group of weapon or aircraft firing condition parameters, uploading, to the aircraft, the coefficients of the identified best candidate polynomial selecting by a reconstructor on the aircraft containing the same generic algorithm, coefficients according to conditions of the aircraft and the target if the aircraft and the target are within the performance envelope of the weapon, according to the conditions; and using the selected coefficients, generating the feasibility display.

A feasibility display indicative of a feasibility of a weapon carried on the aircraft successfully engaging a target and/or a feasibility of a weapon carried on the target successfully engaging the aircraft is cooperatively generated by an aircraft and another device. The another device has a database describing a performance envelope of the weapon. The another device identifies a best candidate polynomial from a plurality of candidate polynomials based on respective scores using a genetic algorithm. Each score is based on a quality of fit of the candidate polynomial to a characteristic of the performance envelope of the weapon. The another device uploads, after a plurality of characteristics are evaluated, to the aircraft coefficients which are determined for the best candidate polynomial. Variables of the plurality are some or all of a weapon or aircraft firing condition parameters. The aircraft uses selected coefficients to generate the feasibility display.

The invention relates to a system and method for detecting anomalous system behaviour. The system comprises a plurality of sensors and a trained autoencoder. The method of training comprises: obtaining training data and test data comprising multiple data records for at least one engineering asset which corresponds to the engineering asset whose behaviour is to be classified, wherein the data records comprise a plurality of sensor readings for the engineering asset; fitting the autoencoder to the obtained training data; running the test data through the encoder of the fitted autoencoder to obtain encodings of the test data; generating a plurality of data sets from the obtained encodings, wherein the generated plurality of data sets include under-represented data sets; cloning the fitted autoencoder to create a cloned autoencoder for each of the generated plurality of data sets; and aggregating the cloned autoencoders to form an over-arching autoencoder. The method further comprises calculating an error data set between the training data and data reconstructed by the over-arching auto encoder; obtaining, using the calculated error data set, estimated parameters for calculating an anomaly score for each data record, wherein the anomaly score is selected from a Mahalanobis distance and a squared Mahalanobis distance; and estimating, using the calculated error set, parameters for calculating a decomposition of the anomaly score to identify a contribution from each sensor reading to the anomaly score.

There is disclosed an aircraft configured to collect air data, the aircraft comprising: a wing structure; a forebody, forward of the wing structure; an afterbody, backward of the forebody; a skin covering the wing, the forebody and the afterbody; at least one recess formed at the skin, the recess being configured to affect the pressure of air flowing at the recess; at least one ambient sensor port for measuring ambient air pressure at the skin; and at least one recess sensor port for measuring the air pressure at the recess.

An aircraft emergency control system comprises at least one sensor configured to output an electronic signal relating to detection of incapacitation of at least one aircraft crew member. A processor is configured to receive and process the electronic signal to determine whether emergency action is to be taken. A control unit is configured to communicate, in use, a control signal to an avionics system of the aircraft in relation to the emergency action if the processor determines that emergency action is to be taken.

There is disclosed an aircraft configured to collect air data, the aircraft comprising: a wing structure; a forebody, forward of the wing structure; an afterbody, backward of the forebody; a skin covering the wing, the forebody and the afterbody; at least one recess formed at the skin, the recess being configured to affect the pressure of air flowing at the recess; at least one ambient sensor port for measuring ambient air pressure at the skin; and at least one recess sensor port for measuring the air pressure at the recess.

Disclosed is an apparatus for testing a device, comprising: a switch ( 100 ) arranged to replace a circuit breaker ( 30 ) associated with an individual system in the device under test, wherein the switch ( 100 ) is operable to be controlled remotely from the device under test such that the switch ( 100 ) either activates or deactivates the individual system.

A data processing method and apparatus, the method comprising: storing, at a first memory location in a memory, a first copy of a set of data; storing, at a second memory location in a memory, a second copy of a set of data; comparing the first copy to the second copy so as to identify, within the first copy, a pointer, the pointer being located at a first data element of the first copy, the pointer specifying a second data element of the first copy; determining an offset for the identified pointer, the offset specifying a number of data elements between the first data element and the second data element; and modifying the first copy such that the pointer within the first copy specifies the second data element using only the first data element and the offset.