Patent Description:
Optical air data systems can measure air density because of the proportionality between the air density and the molecular signal backscatter intensity. If the air temperature is also known, the static air pressure can be calculated with the Ideal Gas Law. Calculating static air density and pressure from the molecular signal backscatter intensity is performed using conversion coefficients. The conversion coefficients are determined from various quantities, such as laser power, transmitter-receiver alignment, aperture size, and optical element throughput. In general, these quantities may vary due to known or unknown effects. Therefore, the conversion coefficients may need to be calibrated frequently. Current approaches require regular system recalibration, which requires the need for certified devices and causes high maintenance costs. <CIT> and <CIT> disclose system comprising a pressure air data system mounted on a vehicle.

A system comprises a pressure air data system mounted on a vehicle and including one or more non-optical air data sensors, wherein the one or more non-optical air data sensors are configured to interrogate a region of interest outside of the vehicle to determine a first set of air data measurements comprising at least a first static air pressure. The system also includes an optical air data system mounted on the vehicle and comprising one or more optical air data sensors, wherein the one or more optical air data sensors are configured to interrogate the region of interest to determine a second set of air data measurements comprising at least a second static air pressure. The second static air pressure is determined using one or more conversion coefficients. At least one system processor is operatively coupled to the pressure air data system and the optical air data system. The system processor is operative to receive and process the first static air pressure from the pressure air data system; receive and process the second static air pressure from the optical air data system; dynamically recalibrate the one or more conversion coefficients by computing at least one correction factor for the optical air data system; send the correction factor to the optical air data system to update the second static air pressure; and output an optimized static air pressure based on the first static air pressure and the updated second static air pressure. The optical air data system is configured to be used as a backup in case of failure of the pressure air data system.

In the following detailed description, embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It is to be understood that other embodiments may be utilized without departing from the scope of the invention. The following detailed description is, therefore, not to be taken in a limiting sense.

A method and system for dynamic recalibration of an optical air data system is described herein.

In order to use an optical air data system to obtain air data measurements such as static air pressure, calibration of conversion coefficients is needed. The calibration needs to be done frequently in order to provide signal outputs with a required precision. The present approach provides a method for dynamic recalibration of the optical air data system. This provides a reduction in the cost of regular maintenance calibration, while improving the performance of the optical air data system.

The present optical air data system can be used as a backup in case of failure of a legacy air data system such as a pressure air data system. The dynamic recalibration of the optical air data system enables a required performance of the optical air data system so it can be used as the main air data system in case of failure of the pressure air data system.

Further details regarding the present approach are described as follows and with reference to the drawings.

<FIG> is a block diagram of a system <NUM> for dynamic recalibration, according to one embodiment. The system <NUM> generally comprises a pressure air data system <NUM> onboard a vehicle <NUM>, such as an aircraft, and an optical air data system <NUM> onboard vehicle <NUM>. An onboard system processor <NUM> is in operative communication with pressure air data system <NUM>, and with optical air data system <NUM>. The system processor <NUM> can include or be in communication with one or more memory units (not shown), which are configured to store program instructions and data.

The pressure air data system <NUM> includes one or more non-optical air data sensors <NUM>, and at least one static pressure processor <NUM> operatively coupled to non-optical air data sensors <NUM>. The non-optical air data sensors <NUM> are configured to interrogate an atmospheric region of interest <NUM> outside of vehicle <NUM>, and to provide sensor data to static pressure processor <NUM>, which determines a first set of air data measurements comprising at least a first static air pressure <NUM>.

In example embodiments, non-optical air data sensors <NUM> can include one or more static pressure sensors such as pitot tubes, static ports, or the like. In addition, one or more temperature sensors <NUM> can be optionally employed in pressure air data system <NUM>.

The optical air data system <NUM> includes one or more optical air data sensors <NUM>, and at least one optical air data processor <NUM> operatively coupled to optical air data sensors <NUM>. The optical air data sensors <NUM> are configured to interrogate region of interest <NUM>, and to provide sensor data to optical air data processor <NUM>, which determines a second set of air data measurements comprising at least a second static air pressure <NUM>. The second static air pressure <NUM> is determined using one or more conversion coefficients <NUM>, as discussed in further detail hereafter.

In example embodiments, optical air data sensors <NUM> can include one or more light detection and ranging (LiDAR) sensors, which are configured to transmit light into region of interest <NUM>, and collect a scattered portion of the transmitted light from region of interest <NUM>. In addition, one or more temperature sensors <NUM> can be optionally employed in optical air data system <NUM>.

The system processor <NUM> is operative to receive and process the first static air pressure <NUM> from pressure air data system <NUM>. The system processor <NUM> is also operative to receive and process the second static air pressure <NUM> from optical air data system <NUM>. In one embodiment, processor <NUM> hosts a Kalman filter <NUM>, which can be used to dynamically recalibrate conversion coefficients <NUM> by computing a correction factor <NUM>, which is output to optical air data system <NUM>. The Kalman filter <NUM> is also operative to estimate a best static pressure output from pressure air data system <NUM> and optical air data system <NUM>. Further details related to the Kalman filter are discussed hereafter.

The correction factor <NUM> is applied to recalibrate conversion coefficients <NUM> such that an updated second static air pressure <NUM> is output by optical air data system <NUM> in the next measurement cycle. The processor <NUM> outputs an optimized static air pressure <NUM> based on the first static air pressure <NUM> from pressure air data system <NUM>, and the updated second static air pressure <NUM> from optical air data system <NUM>.

The optical air data system <NUM> can also be configured as a backup air data system in case of failure of pressure air data system <NUM>.

During operation of system <NUM>, optical air data system <NUM> can compute the static air pressure from a molecular signal backscatter intensity using the ideal gas law, expressed as: <MAT> where Pcalc is a calculated pressure, N is the number of air molecules, kb is the Boltzmann constant, T is a static air temperature calculated from the optical air data system, and V is a volume of the measured area.

Because the optical air data system is not directly measuring the number of air molecules, but rather the molecular signal backscatter intensity, the number of air molecules can be calculated as: <MAT>.

In case of failure of the pressure air data system <NUM>, optical air data system <NUM> does not update the conversion constant, but instead uses the latest conversion constant to maintain the best performance possible.

<FIG> is a functional flow diagram of a dynamic recalibration process <NUM> performed by a Kalman filter, according to an exemplary implementation. In process <NUM>, the Kaman filter is operative to receive and process a first static air pressure from the pressure air data system (block <NUM>); and receive and process a second static air pressure from the optical air data system (block <NUM>). Thereafter, the Kalman filter dynamically recalibrates conversion coefficients by computing a correction factor for the optical air data system (block <NUM>), based on the first and second static air pressures. The Kalman filter sends the correction factor to the optical air data system to update the second static air pressure in a next measurement cycle (block <NUM>). Subsequently, the Kalman filter outputs an optimized static air pressure based on the first static air pressure and the updated second static air pressure (block <NUM>).

<FIG> is a block diagram of a system <NUM> for dynamic recalibration using a Kalman filter, according to another embodiment. The system <NUM> generally comprises a pressure air data system <NUM> onboard a vehicle, and an onboard optical air data system <NUM>. An onboard system processor <NUM> is in operative communication with pressure air data system <NUM>, and with optical air data system <NUM>.

The pressure air data system <NUM> includes non-optical air data sensors configured to interrogate an atmospheric region of interest outside of the vehicle, and to provide sensor data that is used to determine a first static air pressure. The optical air data system <NUM> includes optical air data sensors configured to interrogate the region of interest, and to provide sensor data that is used to determine a second static air pressure. The second static air pressure is determined using one or more conversion coefficients, as described previously.

The system processor <NUM> is operative to receive and process the first static air pressure from pressure air data system <NUM>, and the second static air pressure from optical air data system <NUM>. The processor <NUM> hosts a Kalman filter <NUM>, which is used to dynamically recalibrate the conversion coefficients. The Kalman filter <NUM> includes a prediction module <NUM>, and a correction module <NUM> configured to receive an output from prediction module <NUM>. The prediction module <NUM> is configured to receive and process the first and second static air pressures. The correction module <NUM> receives the output from prediction module <NUM>, which is used to compute a correction factor for recalibrating the conversion coefficients. A correction signal corresponding to the correction factor is sent from correction module <NUM> to an input of optical air data system <NUM>.

The correction factor is applied to recalibrate the conversion coefficients such that an updated second static air pressure is output by optical air data system <NUM> in a next measurement cycle. The processor <NUM> outputs an optimized static air pressure based on the first static air pressure from pressure air data system <NUM>, and the updated second static air pressure from optical air data system <NUM>.

<FIG> is a flow diagram of an exemplary method <NUM> for dynamic recalibration of an optical air data system, which is employed in conjunction with a pressure air data system onboard a vehicle such as an aircraft. The pressure air data system includes non-optical air data sensors, and the optical air data system includes optical air data sensors. The method <NUM> comprises interrogating a region of interest outside of the vehicle, using the non-optical air data sensors, to determine a first set of air data measurements that includes a first static air pressure (block <NUM>); and interrogating the region of interest, using the optical air data sensors, to determine a second set of air data measurements that includes a second static air pressure (block <NUM>). The second static air pressure is determined using one or more conversion coefficients saved in a memory of the optical air data system. The method <NUM> further comprises receiving, in a processor, the first static air pressure from the pressure air data system (block <NUM>); and receiving, in the processor, the second static air pressure from the optical air data system (block <NUM>). Thereafter, method <NUM> computes, in the processor, at least one correction factor for the one or more conversion coefficients in the optical air data system (block <NUM>). The method <NUM> then sends the at least one correction factor to the optical air data system to dynamically recalibrate the one or more conversion coefficients (block <NUM>). The method <NUM> performs updating of the second static air pressure in a next measurement cycle using the recalibrated one or more conversion coefficients (block <NUM>). Subsequently, method <NUM> comprises outputting, from the processor, an optimized static air pressure based on the first static air pressure and the updated second static air pressure (block <NUM>).

The processing units and/or other computational devices used in systems and methods described herein may be implemented using software, firmware, hardware, or appropriate combinations thereof. The processing unit and/or other computational devices may be supplemented by, or incorporated in, specially-designed application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). In some implementations, the processing unit and/or other computational devices may communicate through an additional transceiver with other computing devices outside of the system, such as those associated with a management system or computing devices associated with other subsystems controlled by the management system. The processing unit and/or other computational devices can also include or function with software programs, firmware, or other computer readable instructions for carrying out various process tasks, calculations, and control functions used in the methods and systems described herein.

The methods described herein may be implemented by computer executable instructions, such as program modules or components, which are executed by at least one processor or processing unit. Generally, program modules include routines, programs, objects, data components, data structures, algorithms, and the like, which perform particular tasks or implement particular abstract data types.

Instructions for carrying out the various process tasks, calculations, and generation of other data used in the operation of the methods described herein can be implemented in software, firmware, or other computer readable instructions. These instructions are typically stored on appropriate computer program products that include computer readable media used for storage of computer readable instructions or data structures. Such a computer readable medium may be available media that can be accessed by a general purpose or special purpose computer or processor, or any programmable logic device.

Claim 1:
A system comprising:
a pressure air data system mounted on a vehicle and comprising one or more non-optical air data sensors, wherein the one or more non-optical air data sensors are configured to interrogate a region of interest outside of the vehicle to determine a first set of air data measurements comprising at least a first static air pressure;
an optical air data system mounted on the vehicle and comprising one or more optical air data sensors, wherein the one or more optical air data sensors are configured to interrogate the region of interest to determine a second set of air data measurements comprising at least a second static air pressure, wherein the second static air pressure is determined using one or more conversion coefficients; and
at least one system processor operatively coupled to the pressure air data system and the optical air data system, the at least one system processor operative to:
receive and process the first static air pressure from the pressure air data system;
receive and process the second static air pressure from the optical air data system;
wherein the optical air data system is configured as a backup system in case of failure of the pressure air data system
characterized in that said one system processor is further operative to dynamically recalibrate the one or more conversion coefficients by computing at least one correction factor for the optical air data system;
send the correction factor to the optical air data system to update the second static air pressure; and
output an optimized static air pressure based on the first static air pressure and the updated second static air pressure.