Optical air data system fusion with remote atmospheric sensing.

Abstract

To provide an optical air data system for measuring aerosol and molecular scattering of light.SOLUTION: An optical air data system 110 performs one or more signal analysis and data fusion methods comprising: (a) determining aerosol and / or molecular concentration from received data, modifying a data analysis algorithm to optimize any remaining unknown parameters, and outputting enhanced air data parameters; (b) determining aerosol concentration from the received data, dynamically optimizing hardware settings in the air data system to enhance a signal level and avoid system saturation, and outputting enhanced air data parameters; or (c) determining aerosol and / or molecular concentration from the received data, estimating a confidence level of an air data algorithm, verifying optical health of the air data system, and reporting the optical health to a user.SELECTED DRAWING: Figure 1A

Description

[Background technology]

[0001] Optical air data systems collect optical backscatter from aerosols and air molecules in the atmosphere. Air data parameters such as airspeed, angle of attack (AOA), angle of sideslip (AOS), temperature, and pressure can be derived from the spectral components of the collected backscatter signals, which depend on aerosol and molecular parameters (e.g., aerosol and molecular concentrations). Accurately extracting air data parameters from the collected backscatter signals can be challenging due to the many dependencies and degrees of freedom of model fits to analyze the air data. Summary of the Invention [Problem to be solved by the invention]

[0002] The system includes an optical air data system operative to measure light scattering of aerosols and molecules from the examination region, and an optical instrument separate from the optical air data system, the optical instrument operative to measure light scattering of aerosols and / or molecules from the examination region, and a processor operative to receive data from the optical air data system and data from the optical instrument. The processor is configured to perform one or more methods, including (a) a first signal analysis and data fusion method that includes determining the concentration of aerosols and / or molecules in the inspection area from the received data, modifying a data analysis algorithm to optimize any remaining unknown parameters, and outputting improved air data parameters; (b) a second signal analysis and data fusion method that includes determining the concentration of aerosols or the presence of aerosols in the inspection area from the received data, dynamically optimizing hardware settings in the optical air data system to improve signal levels and avoid system saturation, and outputting improved air data parameters; or (c) a third signal analysis and data fusion method that includes determining the concentration of aerosols and / or molecules or the presence of aerosols and / or molecules in the inspection area from the received data, estimating a confidence level of the air data algorithm in the processor, verifying the optical integrity of the optical air data system, and reporting the optical integrity to an external user. [Brief explanation of the drawings]

[0003] Features of the present invention will become apparent to those skilled in the art from the following description, which refers to the drawings in which: The present invention will be described with additional specificity and detail using the accompanying drawings, with the understanding that the drawings illustrate exemplary embodiments and therefore should not be considered limiting in scope.

[0004] [Figure 1A] FIG. 1A is a block diagram of an optical-air data fusion system, according to one embodiment.

[0005] [Figure 1B] FIG. 1B shows a graphical representation of an exemplary received optical spectrum produced by the air data fusion system of FIG. 1A.

[0006] [Figure 2A] FIG. 2A is a schematic diagram of an optical air data sensor that can be implemented as part of the air data fusion system of FIG. 1A.

[0007] [Figure 2B] FIG. 2B is a plot illustrating an exemplary backscatter spectrum produced by the optical air data sensor of FIG. 2A.

[0008] [Figure 3] FIG. 3 is a block diagram of one exemplary system operation of an optical-air data fusion system.

[0009] [Figure 4] FIG. 4 is a flow diagram of one improved signal analysis and data fusion method that may be performed by a processor in the exemplary system operation of FIG.

[0010] [Figure 5] FIG. 5 is a block diagram of another exemplary system operation of an optical-air data fusion system.

[0011] [Figure 6] FIG. 6 is a flow diagram of another improved signal analysis and data fusion method that may be performed by a processor in the exemplary system operation of FIG.

[0012] [Figure 7] FIG. 7 is a flow diagram of a further method for providing improved signal analysis and data fusion that may be performed by a processor in an optical-air data fusion system. DETAILED DESCRIPTION OF THE INVENTION

[0013] 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 present invention. Accordingly, the following detailed description is not to be taken in a limiting sense.

[0014] Optical air data fusion systems and methods are described herein that utilize remote atmospheric sensing. The systems and methods are implemented to provide fusion of optical data from an optical air data system and an independent optical instrument. One or more data fusion algorithms can be used to improve the calculations of the optical air data system.

[0015] The present approach leverages other optical instruments that remotely measure all or a subset of the atmospheric constituents measured by the optical air data system to improve the performance of the air data system. In one implementation, fusion of data from two airborne remote atmospheric testing instruments that can measure atmospheric conditions by different mechanisms is used.

[0016] As previously mentioned, accurately extracting air data parameters from collected backscatter signals can be challenging due to the large number of dependencies and degrees of freedom in the model fit for analyzing the air data. The present approach provides that a subset of such dependencies are known or can be measured by another mechanism that can reduce the degrees of freedom in the model fit. Reducing the degrees of freedom in the model fit can provide more robust air data parameters and greater reliability (fidelity) under widely varying optical backscatter conditions.

[0017] In one embodiment, the air data fusion system includes an optical air data system that relies on both aerosol and molecular scattering to measure air data parameters, and another independent optical remote sensing device that measures the aerosol and / or air molecules. By using the independent optical remote sensing device to measure the aerosol and / or molecular content in an associated test volume, one or more parameters of the optical air data system may be known, thus improving the fit model to the data.

[0018] In one example, a separate airborne remote sensing instrument mounted on an aircraft can measure the aerosol content of the atmosphere within the area inspected by the aircraft. By knowing the aerosol content of the atmosphere, this information can be used to assist the algorithms of an optical air data system also mounted on the aircraft in distinguishing the portion of total scattering from aerosol-to-molecular scattering.

[0019] In one method of operation, by knowing the aerosol and / or molecular concentrations, the ratio of aerosol to molecular scattering can be calculated and the data analysis algorithm can be adjusted to optimize the remaining unknown parameters, such as the Doppler spectral shift.

[0020] In another method of operation, by knowing the aerosol concentration or presence, hardware settings in the air data system (e.g., photodetector gain) can be dynamically optimized to improve signal levels and avoid system saturation. For example, different detector settings can be controlled to enable operation of the air data system in higher or lower aerosol concentration regions.

[0021] In a further method of operation, by knowing the concentration of aerosols and / or molecules or the presence of aerosols and / or molecules, the confidence level of the air data algorithm can be estimated, validating the health of the optical air data system and outputting to an external user.

[0022] The system provides various technical benefits, including reducing the degrees of freedom in model fitting to analyze air data, thereby improving model fit accuracy and air data output accuracy. The approach can also provide system redundancy information upon which checks can be performed. The system can also provide control over hardware and software settings to optimize operational (collection, processing, etc.) efficiency. The approach can also provide input regarding the confidence level or reliability of the system.

[0023] Other benefits of the present system include increasing the accuracy, reliability, and confidence level of optical air data systems, providing greater value to users. The approach can also facilitate qualification of reliability requirements.

[0024] Further details of various embodiments are described below with reference to the drawings.

[0025] 1A illustrates an optical air data fusion system 100, according to one embodiment. System 100 includes an optical air data system 110 that functions to measure optical scattering of aerosols and molecules from a test air volume 130 in the atmosphere. System 100 also includes a separate optical instrument 120 that provides remote sensing separate from air data system 110. Thus, optical instrument 120 functions to measure optical scattering of aerosols and / or molecules from test air volume 130. At least one processor 140 functions to receive data from air data system 110 and also to receive data from optical instrument 120. Processor 140 functions to perform one or more signal analysis and data fusion methods 142 to provide improved data output, as described in further detail below.

[0026] The air data system 110 includes at least one light source, such as a laser transmitter 112, configured to transmit a light beam 114 into the test air volume 130. A set of receive optics 115 within the air data system 110 is configured to provide at least one receive channel. The receive optics 115 is configured to collect a scattered portion 116 of the transmitted light beam 114 from one or more aerosols 132 and air molecules 134 within the test air volume 130. In one embodiment, the laser transmitter 112 and receive optics 115 may be implemented in an optical transceiver. An optical detector 118 of the air data system 110 is in communication with the receive channel and is configured to receive the collected scattered portion 116. The optical detector 118 functions to measure signal strength as a function of frequency from the scattered portion 116 and convert this data into an electrical signal that is sent to a processor 140 for analysis.

[0027] In one embodiment, air data system 110 is configured for use on a vehicle such as an aircraft. In this embodiment, air data system 110 comprises an optical air data sensor including a laser transmitter and receiving optics mounted on an optical transceiver having at least one line of sight fixed relative to the vehicle's body axis. The optical air data sensor also includes an optical detector.

[0028] The optical instrument 120 includes at least one light source, such as a laser transmitter 122, configured to transmit a light beam 124 into the test air volume 130. A set of receiving optics 125 is configured to provide at least one receiving channel. The receiving optics 125 is configured to collect a scattered portion 126 of the transmitted light beam 124 from one or more aerosols 132 and / or air molecules 134 within the test air volume 130. In one embodiment, the laser transmitter 122 and receiving optics 125 can be implemented as part of an optical transceiver. An optical detector 128 is in communication with the receiving channel and is configured to receive the collected scattered portion 126. The optical detector 128 functions to convert the collected scattered data into an electrical signal that is sent to a processor 140 for analysis.

[0029] In one embodiment, the optical instrument 120 may be implemented in the form of a particle sensor assembly that may be configured for use on a vehicle, such as an airborne vehicle. The particle sensor assembly functions to measure an aerosol scattering coefficient. In this case, the optical detector 128 functions to measure signal strength as a function of time from the scattering portion 126. There are various other optical sensors currently available that utilize optical detection schemes for particles or aerosols. In another embodiment, the optical instrument 120 may be implemented in the form of an optical sensor that functions to measure a molecular scattering coefficient.

[0030] Alternatively, optical instrument 120 may be implemented as a second air data system that includes the features described above for air data system 110. For example, optical instrument 120 may be implemented using an optical air data sensor with a laser transmitter and receiving optics implemented in an optical transceiver, which also includes an optical detector, as described above.

[0031] In some embodiments, air data system 110 and optical instrument 120 are located on the same vehicle. In other embodiments, air data system 110 and optical instrument 120 are located on different vehicles but function to inspect the same atmospheric region.

[0032] In further embodiments, air data system 110 is located on the vehicle and optical instrument 120 is located on the ground to provide terrestrial optical remote sensing. In these embodiments, air data system 110 (on the vehicle) and optical instrument 120 (on the ground) function to inspect the same atmospheric region.

[0033] In an alternative embodiment, optical instrument 120 may optionally be configured to transmit control signals 150 to air data system 110, as shown in Figure 1A. Control signals 150 function to control hardware and software settings within air data system 110 to optimize operational efficiency.

[0034] 1B shows a graphical representation of exemplary received optical spectra produced by air data fusion system 100. Specifically, FIG. 1B shows a graphical representation of received optical spectrum 160 produced by optical air data system 110 and received optical spectrum 170 produced by independent optical instrument 120.

[0035] The received optical spectrum 160 includes a backscattered line shape 162 created by Rayleigh scattering from atmospheric air molecules 134 in the interrogated air volume 130 and by Mie scattering from atmospheric aerosols 132. Both Rayleigh scattering and Mie scattering contribute to the backscattered line shape. The backscattered line shape 162 includes a Mie-scattered contribution in the form of a narrow aerosol peak 164 that protrudes from the Rayleigh-scattered contribution in the form of a broadened base 166.

[0036] Received optical spectrum 170 includes backscattered lineshape 172 created by Mie scattering from aerosols in the atmosphere. Backscattered lineshape 172 includes a Mie scattered contribution in the form of an aerosol peak 174. Received optical spectrum 170 produced by optical instrument 120 is used by processor 140 to help calculate received optical spectrum 160 in air data system 110.

[0037] For example, aerosol peak 1 from optical instrument 120 7 4 helps provide improved signal analysis and data fusion by taking otherwise unconstrained fitting parameters in the air data system that collected the data, such as aerosol and molecular backscatter signal strength, from the optical instrument 120, and constraining these parameters from independent measurements of aerosol backscatter signal strength. This allows data fitting to focus primarily on the Doppler shift in the detected spectrum. Various air data parameters, such as airspeed, angle of attack (AOA), angle of sideslip (AOS), temperature, and pressure, can then be derived from the optical spectrum 160 using standard processing techniques.

[0038] For example, air speed, which is related to the speed of a moving vehicle, is derived from the Doppler shift between the center frequency of the backscattered signal and the laser frequency (discussed further below). Both air temperature and air pressure are convolved with the molecular line width of the backscattered spectrum (i.e., backscattered lineshape 162). The width (w) of the backscattered lineshape 162 is determined by the air temperature. The intensity (i.e., the area under the curve of the backscattered lineshape 162) is determined by the density, which is directly related to the air pressure. Typically, a model is used to fit and then infer air data parameters from the backscattered lineshape 162.

[0039] The calculated air data parameters are output from processor 140 to other systems, such as a vehicle computer, for use in further vehicle data processing. For example, when the vehicle is an aircraft, processor 140 may transmit the estimated airspeed to avionics equipment onboard the aircraft for further data processing.

[0040] 2A is a schematic diagram of an optical air data sensor 210, such as an incoherent hyperspectral (direct detection) sensor, that may be implemented as part of an optical air data system, such as air data system 110 (FIG. 1A). Air data sensor 210 system 210 is designed to perform Doppler velocity measurements from aerosol and molecular backscattering within an interrogation volume 230. Optical air data sensor 210 includes a laser transmitter 212 configured to transmit a light beam having an optical frequency f into interrogation volume 230. Receiver 215 is configured to receive backscattered light from interrogation volume 230, with the received backscattered light having a frequency shift f (i.e., f + δf). Additionally, FIG. 2A illustrates a system where wind speed v wind 2 shows the wind direction 240 into the inspection volume 230, with

[0041] 2B is a plot illustrating an exemplary backscatter spectrum 250 produced by optical air data sensor 210, showing the total backscatter spectrum shifted relative to the received molecular, aerosol, and transmitted laser light. Specifically, backscatter spectrum 250 is shifted relative to transmitted spectrum 244 and differentiated by the contributions shown by curves 254 and 256 of the molecular and aerosol components, respectively. The combined signal measured by the system is shown by curve 258.

[0042] The spectrum of backscattered light S[δf] received by an optical air data system sensitive to aerosol (A) and molecular (M) scattering, with the frequency shift δf≡f-f0 from the received light f and transmitter optical frequency f0, centered at a Doppler shift Δf, may be given by the following equation: S[f]=A[Δf,n A ,f]+M[Δf,n M ,f] n in the formula M , n A are the molecular and aerosol scattering cross sections present in the atmosphere, respectively, and the variables in square brackets represent the function arguments.

[0043] In general, an incoherent hyperspectral system can be modeled by defining S[f] as a function of the free fitting parameter n A , n M , and Δf, air data parameters can be measured. Some air data products are calculated from the molecular backscattering contribution M alone, including but not limited to air temperature and density. However, the aerosol backscattering contribution A may be greater than or equal to M in some atmospheric conditions. In such conditions where A is large, air data parameters derived from the molecular scattering signal alone may be more difficult to measure reliably due to the dominant signal A and its associated noise.

[0044] For example, air data parameters such as temperature and pressure are more sensitive to various types of aerosols, and as a result, measuring temperature and pressure can be challenging in areas with higher aerosol concentrations. In addition, higher aerosol concentrations can reduce the reliability of such temperature and pressure measurements.

[0045] The utility of the fusion techniques described herein is to derive data from secondary data sources such as independent optical instruments. A , which reduces the number of free fitting parameters and A with higher fidelity than if was a free fitting parameter M , Δf can be fitted. Alternatively, n M or n A and n MIf linear combinations of σ and σ are measured by secondary data sources, the same procedure can be used to improve the fit fidelity for the remaining unknown fitting parameters.

[0046] FIG. 3 is a block diagram of one exemplary system operation 300 for an optical air data fusion system, such as air data fusion system 100 (FIG. 1A). FIG. 3 illustrates how a separate optical instrument, such as optical instrument 120, can improve the signal analysis performance of an optical air data system, such as air data system 110, according to one implementation. In this example, air data system 110 acquires aerosol and molecular backscatter signals from the test air volume, and corresponding data signals 312 are transmitted to a processor, such as processor 140. Optical instrument 120 acquires aerosol and / or molecular backscatter signals from the test air volume, and corresponding data signals 314 are transmitted to processor 140. Processor 140 performs an improved signal analysis and data fusion method 320 based on the received data, which is described further below. Processor 140 then outputs improved air data 330, such as improved air data parameters, to one or more other systems for use in further data processing.

[0047] 4 is a flow diagram of an improved signal analysis and data fusion method 320 that can be performed by a processor. Method 320 includes determining the concentration of aerosols and / or molecules in the examined air volume from received data signals (block 410). Method 320 can optionally calculate the ratio of aerosol to molecule scattering, if desired (block 420). The data analysis algorithm is modified to optimize any remaining unknown parameters (block 430). Method 320 then outputs improved air data parameters (block 440).

[0048] FIG. 5 is a block diagram of another exemplary system operation 500 for an optical air data fusion system, such as air data fusion system 100 (FIG. 1A). FIG. 5 illustrates how, according to another implementation, a separate optical instrument, such as optical instrument 120, can assist with the hardware configuration and / or improve the signal analysis performance of the optical air data system to provide an improved air data system 110. In this example, air data system 110 acquires aerosol and molecular backscatter signals from the test air volume, and optical instrument 120 acquires the aerosol and / or molecular backscatter signals from the test air volume. Additionally, optical instrument 120 generates a hardware control signal 510 based on the aerosol and / or molecular backscatter signals. The hardware control signal 510 is transmitted to air data system 110 to assist in generating an improved aerosol and molecular backscatter signal, and a corresponding improved data signal 512 is transmitted from air data system 110 to processor 140.

[0049] Data signals 514 corresponding to the acquired aerosol and / or molecular backscatter signals may also be transmitted from optical instrument 120 to processor 140. Processor 140 then performs an improved signal analysis and data fusion method 520 based on the received data, which is described further below. Processor 140 then outputs improved air data 530, such as improved air data parameters, to one or more other systems for use in further data processing.

[0050] 6 is a flow diagram of an improved signal analysis and data fusion method 520 that can be performed by a processor. Method 520 includes determining the concentration or presence of aerosols in the examination region from received data (block 610). Method 520 dynamically optimizes hardware settings in the optical air data system to improve signal levels and avoid system saturation (block 620). Method 520 then outputs improved air data parameters.

[0051] 7 is a flow diagram of another method 700 for providing improved signal analysis and data fusion that may be performed by a processor. Method 700 includes determining the concentration or presence of aerosols and / or molecules in an examination region from received data (block 710). Method 700 then estimates a confidence level of the air data algorithm in the processor (block 720). Method 700 verifies the optical health of the optical air data system (block 730) and reports the optical health to an external user (block 740).

[0052] The computers or processors used in the present system may be implemented using software, firmware, hardware, or any suitable combination thereof, as will be known to those skilled in the art. They may be supplemented by or incorporated in specially designed application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs). The computers or processors may also include software programs, firmware, or other computer-readable instructions for performing various process tasks, computations, and control functions used in the present systems and methods.

[0053] The methods may be implemented by computer-executable instructions, such as program modules or components, that are executed by at least one processor. Generally, program modules include routines, programs, objects, data components, data structures, algorithms, and the like that perform particular tasks or implement particular abstract data types.

[0054] Instructions for performing various process tasks, calculations, and generating other data used in the operation of the methods described herein may be implemented in software, firmware, or other computer-readable or processor-readable instructions. These instructions are typically stored in any suitable computer program product, including computer-readable media used for storing computer-readable instructions or data structures. Such computer-readable media may be any available media that can be accessed by a general-purpose or special-purpose computer or processor, or any programmable logic device.

[0055] Suitable processor-readable media may include storage or memory media such as magnetic or optical media, for example, conventional hard disks, compact discs, DVDs, Blu-ray discs, or other optical storage media, volatile or non-volatile media such as random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory, and the like, or any other medium that can be used to carry or store desired program code in the form of computer-executable instructions or data structures. Illustrative Embodiments

[0056] Example 1 includes an optical air data system operative to measure light scattering of aerosols and molecules from an examination region; an optical instrument separate from the optical air data system, the optical instrument operative to measure light scattering of aerosols and / or molecules from the examination region; and a processor operative to receive data from the optical air data system and data from the optical instrument, the first signal analysis and data fusion method including: (a) determining the concentration of aerosols and / or molecules in the examination region from the received data, modifying a data analysis algorithm to optimize any remaining unknown parameters, and outputting the improved air data parameters; and (b) determining the concentration of aerosols or molecules in the examination region from the received data. and a processor configured to perform one or more methods, including (c) a second signal analysis and data fusion method that includes determining the presence of aerosols, dynamically optimizing hardware settings in the optical air data system to improve signal levels and avoid system saturation, and outputting improved air data parameters; or (c) a third signal analysis and data fusion method that includes determining the concentration of aerosols and / or molecules or the presence of aerosols and / or molecules in the inspection area from the received data, estimating a confidence level of the air data algorithm in the processor, verifying the optical health of the optical air data system, and reporting the optical health to an external user.

[0057] Example 2 includes the system of Example 1, wherein the optical air data system includes: a first light source configured to transmit a first light beam into the test air volume; a first set of receiving optics providing a first receiving channel, the first set of receiving optics configured to collect a first scattered portion of the transmitted first light beam from one or more aerosols and air molecules in the test air volume; and a first optical detector in communication with the first receiving channel and configured to receive the collected first scattered portion, the first optical detector functioning to convert the first scattered portion into a first data signal sent to a processor for analysis.

[0058] Example 3 includes the system of example 2, wherein the first light source comprises a first laser transmitter.

[0059] Example 4 includes the system of example 3, wherein the first laser transmitter and the first set of receiving optics are implemented in a first optical transceiver.

[0060] Example 5 includes the system of any of examples 1-4, wherein the optical air data system comprises an incoherent hyperspectral system.

[0061] Example 6 includes the system of any of Examples 2-5, wherein the optical instrument includes: a second light source configured to transmit a second light beam into the test air volume; a second set of receiving optics providing a second receiving channel, the second set of receiving optics configured to collect a second scattered portion of the transmitted second light beam from one or more aerosols and / or air molecules in the test air volume; and a second optical detector in communication with the second receiving channel and configured to receive the collected second scattered portion, the second optical detector functioning to convert the second scattered portion into a second data signal sent to a processor for analysis.

[0062] Example 7 includes the system of example 6, wherein the second light source comprises a second laser transmitter.

[0063] Example 8 includes the system of example 7, wherein the second laser transmitter and the second set of receiving optics are implemented in a second optical transceiver.

[0064] Example 9 includes the system of any of examples 1-5, wherein the optical instrument includes a particle sensor assembly.

[0065] Example 10 includes the system of example 9, wherein the particle sensor assembly functions to measure the aerosol scattering coefficient.

[0066] Example 11 includes the system of any of examples 1-8, wherein the optical instrument comprises an optical sensor operative to measure a molecular scattering coefficient.

[0067] Example 12 includes the system of any of Examples 1-11, wherein the optical air data system and the optical instrument are mounted on one or more vehicles, or the optical air data system is mounted on the vehicle and the optical instrument is on the ground.

[0068] Example 13 includes the system of example 12, wherein the one or more vehicles include an aircraft.

[0069] Example 14 includes the system of any of Examples 1 to 13, wherein the optical device is configured to send control signals to the air data system, and the control signals function to control hardware and software settings in the optical air data system to optimize operating efficiency.

[0070] Example 15 includes a method including: acquiring a first backscattered signal from one or more aerosols and air molecules in the test air volume using an optical air data system that generates a first data signal corresponding to the first backscattered signal; transmitting the first data signal to a processor; acquiring a second backscattered signal from one or more aerosols and / or air molecules in the test air volume using an optical instrument that generates a second data signal corresponding to the second backscattered signal; transmitting the second data signal to the processor; performing an improved signal analysis and data fusion method in the processor based on the first and second data signals; and outputting one or more improved air data parameters from the processor.

[0071] Example 16 includes the method of example 15, wherein the improved signal analysis and data fusion method includes determining aerosol and / or molecule concentrations in the examination region from the first and second data signals, and modifying the data analysis algorithm to optimize any remaining unknown parameters.

[0072] Example 17 includes a method according to any of Examples 15-16, wherein the improved signal analysis and data fusion method includes determining the concentration of or presence of aerosols in the inspection region from the first and second data signals, and dynamically optimizing hardware settings in the optical air data system to improve signal levels and avoid system saturation based on a control signal from the optical instrument.

[0073] Example 18 includes a method according to any of Examples 15-17, wherein the improved signal analysis and data fusion method includes determining the concentration of aerosols and / or molecules or the presence of aerosols and / or molecules in the inspection area from the first and second data signals, estimating a confidence level of the air data algorithm in the processor, verifying the optical health of the optical air data system, and reporting the optical health to an external user.

[0074] Example 19 includes the method of any of examples 15-18, wherein the optical air data system and the optical instrument are mounted on one or more vehicles.

[0075] Example 20 includes the method of any of examples 15-18, wherein the optical air data system is mounted on a vehicle and the optical instrument is on the ground.

[0076] The present invention may be embodied in other specific forms without departing from its essential characteristics. The described embodiments are to be considered merely as illustrative and not limiting. The scope of the present invention is therefore indicated by the appended claims, rather than the foregoing description. All changes that come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims

1. 1. A system comprising: an optical air data system operable to measure light scattering of aerosols and molecules from the examination region using a first photodetector; an optical instrument separate from the optical air data system, the optical instrument operable to measure light scattering of aerosols and / or molecules from the examination area using a second optical detector, the field of view of the first optical detector and the field of view of the second optical detector overlapping at the examination area; a processor operative to receive data from the optical air data system and data from the optical instrument, determining the concentration or presence of aerosols in the test area from the data received from the optical air data system and the optical instrument; dynamically optimizing detector settings in the optical air data system by adjusting detector settings to improve signal levels and avoid system saturation; and outputting improved air data parameters.

2. the optical instrument comprises a particle sensor assembly operable to measure an aerosol scattering coefficient; or The system of claim 1 , wherein the optical instrument comprises an optical sensor operable to measure a molecular scattering coefficient.

3. 1. A method comprising: acquiring a first backscattered signal from one or more aerosols and air molecules within the examination region using an optical air data system that generates a first data signal corresponding to the first backscattered signal; transmitting the first data signal to a processor; acquiring second backscattered signals from one or more aerosols and / or air molecules within the examination region using an optical instrument that generates second data signals corresponding to the second backscattered signals; transmitting the second data signal to the processor; a field of view of the optical air data system and a field of view of the optical instrument overlap in the inspection area; determining a concentration or presence of aerosol in the examination region from the first and second data signals; performing with the processor a data fusion method comprising: dynamically optimizing detector settings in the optical air data system by adjusting detector settings to increase signal levels and avoid system saturation; and outputting from the processor one or more improved air data parameters.

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