Patent Description:
The present disclosure relates to the field of flight control systems, methods, and apparatuses; even more particularly, to systems, methods, and apparatuses for sensing terrain or obstacles in flight in degraded visual environments (DVE). In one aspect, the disclosure describes new and novel systems and methods for applying LIDAR with a spatial light modulator (SLM) to match the emitted light profile adaptively to the backscatter from the DVE, thereby improving the signal return from the terrain or obstacle of interest and allowing detection at longer ranges in DVEs.

LIDAR, sometimes referred to as "lidar," "LiDAR," or a "laser scanner," is a combination of the words "light" and "radar," but also can be considered an acronym for "Light Detection and Ranging" or "Light Imaging, Detection, and Ranging. " LIDAR generally refers to a ranging technique where a laser beam is aimed at a target and the reflected return of the laser beam is measured to determine distance to that target. By scanning the laser beam, returns can be compiled into accurate 3D models of the environment. LIDAR is useful in aviation both for generating accurate 3D maps of terrain for future use (e.g., mapping), and for real time terrain and object detection for collision avoidance.

Objects of interest are relatively poor reflectors of coherent light beams, such as a laser beam; therefore the light return to the LIDAR instrument may be in the form of scattered reflections, often called "backscatter. " Scattered light that makes its way back to the detector of the LIDAR instrument indicates a return from a target. Because clear air scatters the laser light much less than solid surfaces, the time of arrival of a peak in the backscatter energy can be used to determine a distance to the target toward which the LIDAR is aimed. Light that takes an indirect path, typically because it is reflected by interaction with molecules in the air (whether on the way to or from the target), interferes with the direct path response to the target. Nevertheless, in clear air LIDAR works very well and can be used to make high resolution images of a surface at relatively long ranges.

LIDAR's accuracy is degraded, however, when the air or "medium" contains additional media, such as molecules of smoke, water, dust, or the like, which tend to further scatter light at the frequency of the laser being used. Thus, conditions such as rain, dust, heavy pollution, or fog, that cause a degraded visual environment (DVE), also significantly reduce the effective range of LIDAR, because the background level of backscatter returns increases rapidly with distance through the DVE to the point where the backscatter from the media cannot be distinguished from photons reflected by the target, both because the background backscatter is greatly increased and the amount of laser illumination that can be reflected by the target is greatly reduced by the round trip of the laser beam through the medium. For real-time scenarios, such as the operation of autonomous aerial vehicles that must land in a DVE, or pilot visualization aids in DVE situations, this loss of capability presents an obstacle to sustaining operations in DVE environments.

Thus, a need exists for a LIDAR system that will continue to perform in DVE environments with better object detection and resolution than is achieved with current techniques for overcoming DVE in LIDAR.

<CIT>) states in its abstract: a method is presented utilizing a holographic approach for linear phase conjugation to compensate for atmosphere-induce aberrations that severely limit laser performance. In an effort to improve beam quality, fine aim point control, and laser energy delivered to the target, aberration compensation is accomplished using holographic adaptive tracking that utilizes a spatial light modulator as a dynamic wavefront-reversing element to undo aberrations induced by the atmosphere, platform motion, or both. This aberration compensation technique results in a high fidelity, near-diffraction limited laser beam delivered to the target.

The invention to which this European patent is directed is defined in the appended independent claims. The present disclosure describes, inter alia, a light focusing through degraded visual environment (LIFT-DVE) LIDAR system that will enable greater mission capabilities in DVEs, such as rain, brown-out, low light, and similar conditions. For example, a LIDAR system may include a spatial light modulator (SLM) at the light source that corrects the emitted laser wave front to decrease the impact of the scattering media in a DVE and allowing visualization of target objects in or beyond the DVE.

According to a first aspect, a LIDAR system for an aerial vehicle operating in a degraded visual environment (DVE) comprises: a laser source configured to emit a coherent light beam; a spatial light modulator to modulate said coherent light beam, wherein the spatial light modulator is configured to phase conjugate an interference pattern of a DVE medium that is positioned between said spatial light modulator and a target; an optical lens to filter said coherent light beam from the spatial light modulator, wherein the optical lens is configured to direct the coherent light beam toward the target, wherein the coherent light beam reflects off of the DVE medium to yield scattered photons and reflects off of the target to yield reflected photons; a second optical lens to collect the scattered photons and the reflected photons; and a detector array to detect the scattered photons and the reflected photons. The LIDAR system is configured to iteratively scan a plurality of conjugates to identify a current scattering property of said DVE medium. The step for iteratively scanning the plurality of conjugates uses a Fienup reconstruction technique. The LIDAR system is configured to probe at successively longer presumed ranges until a predetermined time for a scan exceeds a decorrelation time of said DVE medium at a presumed distance.

In certain examples, the LIDAR iteratively scans all possible conjugates to identify a current scattering state of said DVE medium.

In certain examples, the laser source is configured to emit the coherent light beam via an optical phase array.

In certain examples, the detector array is a single photon avalanche diode (SPAD) array.

In certain examples, the detector array and the spatial light modulator are each operatively coupled to a digital signal processor, wherein the digital signal processor is configured to communicate with a flight control system of the aerial vehicle.

In certain examples, the flight control system is configured to identify a landing zone as a function of data received from the LIDAR system via the digital signal processor.

In certain examples, the optical lens includes a beam splitter to create a reference beam to which the scattered photons or the reflected photons can be compared.

In certain examples, the digital signal processor is configured to track a position and pose of the aerial vehicle as the aerial vehicle navigates through the DVE medium.

In certain examples, the digital signal processor is configured to track the position and pose based at least in part on information received from the flight control system.

According to a second aspect, a method of operating a LIDAR system of an aerial vehicle operating in a degraded visual environment (DVE) comprises the steps of: emitting a coherent light beam from a laser source; modulating said coherent light beam via a spatial light modulator, wherein the spatial light modulator is configured to phase conjugate an interference pattern of a DVE medium that is positioned between said spatial light modulator and a target; filtering said coherent light beam from the spatial light modulator via an optical lens; directing the coherent light beam toward the target, wherein the coherent light beam reflects off of the DVE medium to yield scattered photons and reflects off of the target to yield reflected photons; collecting the scattered photons and the reflected photons via a second optical lens; and detecting the scattered photons and the reflected photons via a detector array. The method further comprises the step of iteratively scanning a plurality of conjugates to identify a current scattering property of said DVE medium. The step for iteratively scanning the plurality of conjugates uses a Fienup reconstruction technique. The method further comprises the step of probing at successively longer presumed ranges until a predetermined time for a scan exceeds a decorrelation time of said DVE medium at a presumed distance.

In certain examples, the method further comprises the step of iteratively scanning all possible conjugates to identify a current scattering property of said DVE medium.

In certain examples, the method further comprises the step of identifying a landing zone as a function of data received from the LIDAR system via the digital signal processor.

In certain examples, the optical lens includes a beam splitter to create a reference beam and the method further comprises the step of comparing the reference beam to the scattered photons or the reflected photons.

In certain examples, the method further comprises the step of tracking a position and pose of the aerial vehicle as the aerial vehicle navigates through the DVE medium.

In certain examples, the tracking of the position and pose is based at least in part on information received from the flight control system.

According to an example cited only to understand the invention to which this European patent is directed, a LIDAR system for an aerial vehicle operating in a degraded visual environment (DVE) comprises: a digital signal processor; a laser source configured to emit a coherent light beam; a spatial light modulator operatively coupled to the digital signal processor and configured to modulate said coherent light beam, wherein the spatial light modulator is configured to phase conjugate an interference pattern of a DVE medium that is positioned between said spatial light modulator and a target, and wherein the LIDAR system is configured to direct the coherent light beam toward the target such that the coherent light beam reflects off of the DVE medium to yield scattered photons and reflects off of the target to yield reflected photons; and a detector array operatively coupled to the digital signal processor and configured to detect the scattered photons and the reflected photons, wherein the digital signal processor is configured to track a position and pose of the aerial vehicle as the aerial vehicle navigates through the DVE medium.

In certain examples, the digital signal processor is configured to communicate with a flight control system of the aerial vehicle.

In certain examples, the LIDAR system is configured to iteratively scan a plurality of conjugates to identify a current scattering state of said DVE medium.

In certain examples, the LIDAR iteratively scans all possible conjugates to identify a current scattering state of said DVE medium.

In certain examples, the step for iteratively scanning the plurality of conjugates uses a Fienup reconstruction technique.

In certain examples, the LIDAR system is configured to probe at successively longer presumed ranges until a predetermined time for a scan exceeds a decorrelation time of said DVE medium at a presumed distance.

These and other advantages of the present disclosure may be readily understood with the reference to the following specifications and attached drawings wherein:.

Preferred embodiments of the present disclosure will be described hereinbelow with reference to the accompanying drawings. The components in the drawings are not necessarily drawn to scale, the emphasis instead being placed upon clearly illustrating the principles of the present embodiments. For instance, the size of an element may be exaggerated for clarity and convenience of description. Moreover, wherever possible, the same reference numbers are used throughout the drawings to refer to the same or like elements of an embodiment. In the following description, well-known functions or constructions are not described in detail because they may obscure the disclosure in unnecessary detail. No language in the specification should be construed as indicating any unclaimed element as essential to the practice of the embodiments. For this disclosure, the following terms and definitions shall apply.

As used herein, the words "about" and "approximately," when used to modify or describe a value (or range of values), mean reasonably close to that value or range of values. Thus, the embodiments described herein are not limited to only the recited values and ranges of values, but rather should include reasonably workable deviations. As utilized herein, circuitry or a device is "operable" to perform a function whenever the circuitry or device comprises the necessary hardware and code (if any is necessary) to perform the function, regardless of whether performance of the function is disabled, or not enabled (e.g., by a user-configurable setting, factory trim, etc.).

As used herein, the terms "aerial vehicle" and "aircraft" refer to a machine capable of flight, including, but not limited to, both traditional runway and vertical takeoff and landing ("VTOL") aircraft. VTOL aircraft may include fixed-wing aircraft (e.g., Harrier jets), rotorcraft (e.g., helicopters), and/or tilt-rotor/tilt-wing aircraft.

As utilized herein the terms "circuits" and "circuitry" refer to physical electronic components (i.e., hardware) and any software and/or firmware ("code") which may configure the hardware, be executed by the hardware, and or otherwise be associated with the hardware. As used herein, for example, a particular processor and memory may comprise a first "circuit" when executing a first set of one or more lines of code and may comprise a second "circuit" when executing a second set of one or more lines of code.

As used herein, the terms "communicate" and "communicating" refer to (<NUM>) transmitting, or otherwise conveying, data from a source to a destination, and/or (<NUM>) delivering data to a communications medium, system, channel, network, device, wire, cable, fiber, circuit, and/or link to be conveyed to a destination.

As used herein, the terms "coupled," "coupled to," and "coupled with" as used herein, each mean a relationship between or among two or more devices, apparatuses, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, and/or means, constituting any one or more of: (i) a connection, whether direct or through one or more other devices, apparatuses, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, or means; (ii) a communications relationship, whether direct or through one or more other devices, apparatuses, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, or means; and/or (iii) a functional relationship in which the operation of any one or more devices, apparatuses, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, or means depends, in whole or in part, on the operation of any one or more others thereof.

As used herein, the term "database" as used herein means an organized body of related data, regardless of the manner in which the data or the organized body thereof is represented. For example, the organized body of related data may be in the form of one or more of a table, a map, a grid, a packet, a datagram, a frame, a file, an e-mail, a message, a document, a report, a list, or data presented in any other form.

As used herein, the term "network" as used herein includes both networks and inter-networks of all kinds, including the Internet, and is not limited to any particular network or inter-network.

As used herein, the term "processor" as used herein means processing devices, apparatuses, programs, circuits, components, systems, and subsystems, whether implemented in hardware, tangibly embodied software, or both, and whether or not it is programmable. The term "processor" as used herein includes, but is not limited to, one or more computing devices, hardwired circuits, signal-modifying devices and systems, devices and machines for controlling systems, central processing units, programmable devices and systems, field-programmable gate arrays, application-specific integrated circuits, systems on a chip, systems comprising discrete elements and/or circuits, state machines, virtual machines, data processors, processing facilities, and combinations of any of the foregoing.

With reference to <FIG>, a LIDAR system, such as the disclosed DVE-resistant LIDAR system <NUM>, may be used to navigate an aerial vehicle <NUM> and to identify one or more targets <NUM> (e.g., targets 114a, 114b). Improving the accuracy of the LIDAR systems in a DVE increases the safety and accuracy of aerial-vehicle operation. Existing LIDAR systems can saturate its receiver when subject to a reflected return <NUM> that is backscattered by DVE media <NUM> (e.g., scattering media or scatterers), thereby reducing the accuracy of the LIDAR system while making it difficult to control and/or navigate the aerial vehicle <NUM>. For example, if a traditional LIDAR system were to aim a laser beam <NUM> (or another coherent light beam) at alternate touchdown zone <NUM>, the DVE media <NUM> would result in backscatter of the reflected return <NUM>, which could render the reflected return <NUM> inaccurate and/or undetected. The DVE media <NUM> may be, for example, rain, dust, heavy pollution, fog, etc. Traditional LIDAR systems attempt to address (or otherwise mitigate) this backscatter from DVE media <NUM> by performing adaptive gain control to maximize the perceived target returns, while minimizing the gain applied to backscatter returns; however, this adaptive gain control is difficult to accomplish in real time to allow for effective use of the LIDAR system in flight critical situations, such as landing and collision avoidance.

To provide for real-time operation, a LIDAR system may include a light focusing through degraded visual environment (LIFT-DVE) system and/or functionality to yield the DVE-resistant LIDAR system <NUM>, thereby enabling improved autonomous and/or controlled flight operations. The DVE-resistant LIDAR system <NUM> mitigates DVE effect on its LIDAR components (e.g., the detector) by, inter alia, mitigating noise level from backscattering of the reflected return <NUM> on the LIDAR detector cause by DVE media <NUM> and/or other obstructions. Generally speaking, the DVE-resistant LIDAR system <NUM> is designed to make LIDAR adjustments that overcome DVE automatically. By compensating for a DVE, the operating envelope of an autonomous flight vehicle can be expanded, while the operator of a non-autonomous vehicle can obtain better sensor information regarding the surroundings. The DVE-resistant LIDAR system <NUM> is particularly advantageous in landing scenarios where the aerial vehicle <NUM> is tracking ground targets <NUM>, but may be configured for and applied to all phases of flight, especially flight paths that require object or terrain avoidance in DVE situations.

The DVE-resistant LIDAR system <NUM> provides a LIDAR with spatial light modulator (SLM) that changes or corrects a transmitted laser beam <NUM> based at least in part on the detection of backscatter from a target <NUM> and the backscatter detected from the DVE media <NUM>. That is, the SLM can be tuned by the DVE-resistant LIDAR system <NUM> to cancel out the anticipated backscatter returns from the DVE by separately characterizing the backscatter from the DVE media <NUM> and the backscatter from the target <NUM>. In operation, the DVE-resistant LIDAR system <NUM> uses a sensor (e.g., a LIDAR detector) to detect a returned LIDAR signal from both the DVE media <NUM> as well as the target <NUM>. The DVE-resistant LIDAR system <NUM> may then determine a wavefront correction that can be applied to the laser beam <NUM> to minimize effects of backscattering. Based on this information, the DVE-resistant LIDAR system <NUM> uses a spatial light modulator (SLM) to change or modify the profile (e.g., wavefront) of the laser beam <NUM> and maximize the ground returns while minimizing backscattering. The DVE-resistant LIDAR system <NUM> may continuously (e.g., dynamically; in real time or near-real time) update the transmission matrix of the scattering media, performs phase reversal, and updates to maximize target returns as conditions change.

The DVE-resistant LIDAR system <NUM> may be installed in or on an autonomous aerial vehicle <NUM> to improve performance during a DVE condition or a manned aerial vehicle <NUM> (e.g., a crewed aircraft) to improve visibility for the aircrew. The DVE-resistant LIDAR system <NUM> may be integrated with the aerial vehicle <NUM> as a sensor package (e.g., a sensor payload/sensor suite, which may further include a processor and/or other supporting hardware). The DVE-resistant LIDAR system <NUM> and/or sensor package may be moveably coupled to the aerial vehicle <NUM> via, for example, a gimbal or other structure configure to aim/direct the LIDAR system toward a target <NUM>. In operation, the DVE-resistant LIDAR system <NUM> aims (e.g., via a gimbal) a laser beam <NUM> or another coherent light beam at a target <NUM> and measures the reflected return <NUM> to determine distance between the DVE-resistant LIDAR system <NUM> and that target <NUM>. While the aerial vehicle <NUM> is illustrated as a VTOL aerial vehicle (e.g., a helicopter), the aerial vehicle <NUM> may be a different configuration, such as, for example a fixed-wing aircraft.

The targets <NUM> may be threats, obstacles, and/or touchdown zones (e.g., a primary touchdown zone <NUM>, alternative touchdown zone <NUM>, or an unspecified area to scan for a suitable touchdown zone, etc.) for the aerial vehicle <NUM> to land within a landing zone <NUM>; whether a prepared touchdown zone (e.g., a runway, helipad, etc.) or an unprepared touchdown zone (e.g., natural terrain or ground, a field, a body of water, etc.). For example, the aerial vehicle <NUM> may, in operation, autonomously detect and execute an aerial-vehicle landing at an unprepared touchdown zone based at least in part on data from the DVE-resistant LIDAR system <NUM>, while simultaneously negotiating and navigating threats and obstacles (e.g., vegetation, terrain, buildings, etc.). In other words, LIDAR scanning (via DVE-resistant LIDAR system <NUM>) may be employed to survey the ground (or other terrain) to locate a suitable touchdown zone <NUM>, <NUM>, to detect objects/obstacles, to survey terrain, mapping, autonomous flight, object detection/tracking etc. For example, during LIDAR scanning, the DVE-resistant LIDAR system <NUM> may aim a laser beam <NUM> at a target 114a (i.e., touchdown zone <NUM>) and receive an unobstructed reflected return <NUM>, which may be used to assess the touchdown zone <NUM>. Alternatively, the DVE-resistant LIDAR system <NUM> may aim a laser beam <NUM> at a target 114b (i.e., alternate touchdown zone <NUM>) through DVE media <NUM> and receive an obstructed reflected return <NUM>, which may be processed using the LIFT-DVE system and/or associated techniques disclosed herein.

<FIG> illustrates an example optical path of an optical system <NUM> for the DVE-resistant LIDAR system <NUM> to provide a longer range in a DVE. To transmit a laser beam <NUM> toward a target <NUM> through DVE media <NUM> and back as a reflected return <NUM>, the optical system <NUM> generally comprises a laser light source <NUM>, an optical phase array (OPA) <NUM>, first optics <NUM>, an SLM <NUM>, second optics <NUM>, third optics <NUM>, and a single photon avalanche diode (SPAD) array <NUM>. Each of the first, second, and third optics <NUM>, <NUM>, <NUM> may comprise one or more lenses to focus, adjust, split, and/or otherwise manipulate light passing therethrough. In an illustrative embodiment, the laser light source <NUM> and the OPA <NUM> generate a laser beam <NUM>, which may be modified by an optical SLM <NUM>. For example, the SLM <NUM> can modify the laser beam <NUM> profile to correct and/or account for DVE media <NUM>. To correct and/or account for DVE media <NUM>, the phase modulation on the SLM <NUM> is tied to the received photon energy on the detector (e.g., the SPAD array <NUM>) that is attributed to the DVE media <NUM>. As backscattering photon energy from DVE is received, the SLM <NUM> modifies the laser beam <NUM> to the point of minimum DVE backscatter from the DVE media <NUM>.

Starting at the upper left of the optical system <NUM>, the OPA <NUM> outputs a laser beam 116a, which is filtered by first optics <NUM> to yield a filtered laser beam 116b. The SLM <NUM> is used to modulate the filtered laser beam 116b with a series of patterns defined by a matrix of binary switching elements, thereby yielding a modulated laser beam 116c. Adding a spatial light modulator (SLM) to the LIDAR enables the LIDAR system <NUM> system to tune the profile of the emitted light precisely, thereby canceling out the backscatter from the medium. As the light sensor is co-located with the emitter, the scattering media can be modeled as a 2D matrix, M. By iteratively modulating the SLM <NUM>, the scattering matrix M can be determined, and the SLM <NUM> can modify the emitted light into a mode that gives the phase conjugate of the medium backscatter component at LIDAR a particular focal distance in the DVE using the properties of coherence, similar to optical coherence tomography (OCT).

Second optics <NUM> filter the modulated laser beam 116c to yield a filtered modulated laser beam 116d. At this point, the filtered modulated laser beam 116d exits the LIDAR unit and enters the DVE media <NUM>. The DVE media <NUM> may comprise, for example, a mixture of air and scattering elements (e.g., molecules, particles, etc.) that cause the laser beam <NUM> (e.g., the filtered modulated laser beam 116d) to be scattered before returning to the third optics <NUM> as reflected return <NUM>. Even in the presence of DVE media <NUM>, a fraction of the transmitted laser beam <NUM> (e.g., the filtered modulated laser beam 116d) will reach the target <NUM> and return to third optics <NUM> as a return beam 118a. The return beam 118a passes to the detector (e.g., the SPAD array <NUM>) through the third optics <NUM> as the reflected return 118b.

<FIG> illustrates a block diagram of the DVE-resistant LIDAR system <NUM> relative to other components of an example aerial vehicle <NUM>. As illustrated, the various components of the DVE-resistant LIDAR system <NUM> may be connected to, or incorporated with, a system of the aircraft or another computer system. For example, the LIDAR system <NUM> may be operatively coupled with, whether directly or indirectly, a flight control system <NUM>, one or more steering mechanisms <NUM>, a power supply <NUM>, ISR payload <NUM>, a communication device <NUM>, etc..

The DVE-resistant LIDAR system <NUM> may be operatively coupled with a processor, whether a remote processor or a local processor. For example, the OPA <NUM>, the SLM <NUM>, and the SPAD array <NUM> may be operatively coupled with a digital signal processor (DSP) <NUM>. The DSP <NUM> may, in turn, be operatively coupled with a memory device <NUM> and a user interface <NUM>, as well as other systems, such as the flight control system <NUM>. In operation, the DSP <NUM> interprets data received from the SPAD array <NUM> associated with the reflected return <NUM> to determine the returned LIDAR signal and backscattering. The DSP <NUM> then optimizes the SLM <NUM> to reduce the detected DVE backscattering.

The laser light source <NUM> may be a conventional laser source useful for LIDAR applications that emits a laser beam <NUM> via the OPA <NUM>. The laser beam <NUM> may by pulsed at regular, controlled intervals under the control of the DSP <NUM>. The DSP <NUM> may also control SLM <NUM>, which may be used to create an interference pattern under digital control from the DSP <NUM> of a N x M scattering matrix of controllable binary elements. The SLM <NUM> and pulsing laser beam <NUM> combination should provide a sufficiently high resolution to create a phase conjugate that will cancel the backscatter pattern from the DVE media <NUM>, but that can be iterated through the set of possible conjugates fast enough that a cancelling phase conjugate can be found for a given target depth before the DVE media <NUM> decorrelates or changes and the process is repeated.

A greater number of additional photons will reach the SPAD array <NUM> after reaching the target <NUM>, but being scattered by the DVE media <NUM>. In a DVE, the largest number of photons will be received after being scattered by the DVE media <NUM> without reaching the target <NUM>. By scanning the SLM <NUM> across the available modulation, there will be a best fit phase conjugate of the backscatter generated by the DVE media <NUM> that will leave the photons directly reflected by the target <NUM> at a given depth of focus, if the target <NUM> is there and the moving particles in the DVE media <NUM> do not decorrelate with the best fit SLM modulation before the SLM <NUM> can complete a scan. A peak can be detected and associated with finding the target <NUM> at the direct path photon depth of focus, which can be repeated at that depth over the surrounding area, expanding the areal coverage around the target point.

The DVE-resistant LIDAR system <NUM> system may employ a method of tracking the position and pose of the vehicle as it moves through the scattering media and detects objects in the background. If no target backscatter is detected at a particular distance from the emitter-detector pair within the DVE media <NUM>, the process can then be repeated up to multiple ranges and sampling rate limits of the DVE-resistant LIDAR system <NUM>. This process enables the LIDAR to detect a target at a greater range in DVE than currently possible. As the aerial vehicle <NUM> moves through the DVE media <NUM>, the scattering layer is peeled back to reveal the remaining scattering media and new scattering matrix, M'. In one aspect, a suitable resolution for the SLM <NUM> may be, for example, at least <NUM> x <NUM>, which may be placed between a <NUM> micron wavelength, pulsed laser and the emitting optics. The iteration may be performed on an embedded platform using algorithms, such as a Fienup reconstruction or machine learning based nonlinear beam propagation method, but further including the vehicle position and pose in the software algorithm, which are described in connection with <FIG>. Decorrelation times are dependent on the opacity of the DVE media <NUM> and the total distance through the DVE media <NUM> that is sought to be penetrated. The SPAD array <NUM> acts as a detector and feeds information into the embedded platform (e.g., DSP <NUM>), which calculates the inverse propagation and modifies the phase profile on the SLM <NUM>.

Optics <NUM> assist with focusing and correlating the laser beam <NUM> from the OPA <NUM>. Optics <NUM> may include a beam splitter for creating a reference beam to which returned reflected light (e.g., reflected return <NUM>) can be compared. Optics <NUM> directs and focuses the laser beam <NUM> from the SLM <NUM> into the DVE media <NUM>, where the target <NUM> sought is in (or beyond) the DVE media <NUM> at an unknown distance.

Reflected photons from the target <NUM> and the DVE media <NUM> return to the DVE-resistant LIDAR system <NUM> through focusing optics <NUM>, which directs the gathered light energy to the SPAD array <NUM>. DSP <NUM> processes the signal received from SPAD array <NUM> in view of the current state of SLM <NUM> and scans through a series of proposed ranges to target <NUM> to determine whether a successful conjugation of the scattering properties of the DVE media <NUM> has been achieved that allows for a determination that the target <NUM> has been located or identified. The memory device <NUM>, which is operatively coupled with the DSP <NUM>, may be used to store the algorithms for conjugation of the transmitted beam and the resulting patterns detected. In certain aspects, the algorithms may be based on either Fienup algorithms or machine-learning algorithms based beam propagation methods, which may incorporate the vehicle position and pose into determining the scattering matrix M continuously. Alternatively, the low-level conjugation math may be hardwired into a custom application-specific integrated circuit (ASIC) as hard-connected digital logic to speed processing times and conserve chip area.

In certain aspects, the DVE-resistant LIDAR system <NUM> can be provided with a user interface <NUM> (e.g., a human-machine interface (HMI)) that communicates with and provides information to the operator or monitor that quantifies the degree of scattering caused by the DVE media <NUM> and provides visual and/or audible cues to the operator or a monitor (or monitoring system), particularly in landing zones. The user interface <NUM> can be incorporated into the aerial vehicle <NUM> itself, a portable user device (e.g., a tablet computer, laptop computer, smart phone, etc.), or a remote operations/control center. The user interface <NUM> may allow for the control of the DVE-resistant LIDAR system <NUM>, including activating a DVE mode (instructing to the DVE-resistant LIDAR system <NUM> to employ the LIFT-DVE system and methods), displaying range to a target <NUM> results and/or warnings that the target <NUM> is not detected, and setting the limits of the hardware's search for a target <NUM> in a DVE. The user interface <NUM> is useful for setting the mode of the DVE-resistant LIDAR system <NUM>. For example, the LIDAR can report on its success or failure in probing the DVE media <NUM> and the decorrelation time of the DVE media <NUM>, which gives an assessment of the thickness, depth, or severity of the DVE media <NUM>. The operator can set the DVE-resistant LIDAR system <NUM>, via the user interface <NUM>, for a particular type of DVE media <NUM>, which may range from the most opaque to least opaque environments, for example, so that the LIDAR does not attempt to create a larger or sharper visualization than the optics are capable of resolving in a particular type of DVE. The user interface <NUM> may also report on the state of the hardware (e.g., of the DVE-resistant LIDAR system <NUM>), how old the last accurate ranging measurement is relative to the movement of the vehicle and the extent to which the inertial movement of the aerial vehicle <NUM> exceeds limits of safety given the last known range to the target in the DVE media <NUM>.

The steering mechanism <NUM> may be configured to steer the aerial vehicle <NUM> (whether autonomously or under manned control) on a navigational path to accomplish a mission (e.g., maneuver towards a target <NUM>) or to perform emergency maneuvers (e.g., avoid an obstacle). In one aspect, the steering mechanism <NUM> responds to signals from the flight control system <NUM>, which may employ feedback or other control systems to accurately direct the aerial vehicle <NUM> along an intended route. In relation to VTOL aerial vehicles, the steering mechanism <NUM> may include, for example, a number of rotors (e.g., fans or rotors with helicopters blades), which may be fixed rotors or steerable rotors, along with airfoils and other control surfaces. For other aerial vehicles, such as a fixed-wing aerial vehicle, the steering mechanism <NUM> may include rudders, elevators, flaps, ailerons, spoilers, air brakes, and other control surfaces. For example, rudders at the rear of the aerial vehicle <NUM>, as well as elevators, and any other suitable control surfaces for vertical flight vehicles, along with associated wires, cables, actuators, and so forth. The steering mechanism <NUM> may also include articulated, electric motors employing vectored-thrust control to change the thrust vector directly. The steering mechanism <NUM> may also, or instead, include any mechanism for steering an aerial vehicle <NUM>.

The flight control system <NUM> may determine one or more navigational paths (e.g., generating multiple waypoints) for the aerial vehicle <NUM> to reach a desired location based upon signals received from the components of a navigation system. The flight control system <NUM> may calculate, generate, and send navigation commands (e.g., data signals) to the steering mechanism <NUM> to direct the aerial vehicle <NUM> along a navigational path to the desired location. The flight control system <NUM> may be disposed wholly or partially inside a separate housing, inside the airframe, or some combination thereof. The flight control system <NUM>, which may use information from the DVE-resistant LIDAR system <NUM>, is generally configured to direct, or otherwise control, one or more steering mechanisms <NUM> within an aerial vehicle <NUM>. The flight control system <NUM> may be coupled in a communicating relationship with the aerial vehicle <NUM> and a remote location and may be configured to send and receive signals between the aerial vehicle <NUM> and the remote location via communication device <NUM>. Communication device <NUM> may be, for instance, a wireless transceiver and antenna. In some aspect, one or more flight control system <NUM> may be utilized to accommodate communication among multiple aerial vehicles.

In one example, the flight control system <NUM> may include a steering system <NUM>, a map system <NUM>, a navigation system (e.g., a GPS system <NUM>, an inertial measurement unit (IMU) and/or inertial navigation system (INS)), a flight control processor <NUM>, a gyroscope <NUM>, a flight controller <NUM>, an accelerometer <NUM>, and/or a memory device <NUM>. The flight control system <NUM> may also include the components described above as being disposed within the DVE-resistant LIDAR system <NUM>, as well as other sensors <NUM>, such as any other conventional flight instrumentation, sensors, processing circuitry, communications circuitry, optical system including cameras and the like, necessary or useful for operation of an unmanned aerial vehicle or other autonomously or manually piloted vehicle.

The flight control system <NUM> may be communicatively coupled with the one or more steering mechanisms <NUM> and/or the DVE-resistant LIDAR system <NUM>. For instance, the steering system <NUM> may be configured to receive signals from the flight control system <NUM> (or DVE-resistant LIDAR system <NUM>) and provide suitable control signals to the steering mechanism <NUM> of the vehicle in order to direct the aerial vehicle <NUM> along an intended route.

The map system <NUM> may be part of a map-based flight control system that provides positional information about natural and manmade features within an area. This may include information at any level of detail including, e.g., topographical maps, general two-dimensional maps identifying roads, buildings, rivers, and the like, or detailed, three-dimensional data characterizing the height and shape of various natural and manmade obstructions such as trees, sculptures, utility infrastructure, buildings, and so forth. In one aspect, the map system <NUM> may cooperate with an optical system for visual verification of surrounding context or the map system <NUM> may cooperate with the GPS system <NUM> to provide information on various obstacles within an environment for purposes of path determination or the like. In one aspect, the map system <NUM> may provide a supplemental navigational aid in a GPS-denied or GPS-impaired environment. When GPS is partially or wholly absent, the map system <NUM> may cooperate with the DVE-resistant LIDAR system <NUM> and/or other sensors <NUM>, such as optical sensors, inertial sensors, and so forth to provide positional information until a GPS signal can be recovered.

The map system <NUM> may more generally communicate with other components of the flight control system <NUM> in order to support navigation of a vehicle as contemplated herein. For example, the map system <NUM> may provide a map-based navigation system that stores a map of an operating environment including one or more objects. The map-based navigation system may be coupled to cameras and configured to determine a position of a vehicle by comparing stored objects to a visible environment, which may provide position data in the absence of GPS data or other positional information.

The GPS system <NUM> may be part of a global positioning system configured to determine a position of the aerial vehicle <NUM>. The GPS system <NUM> may include any GPS technology known in the art or that will become known in the art, including conventional, satellite-based systems as well as other systems using publicly or privately operated beacons, positional signals, and the like. The GPS system <NUM> may include one or more transceivers that detect data for use in calculating a location. The GPS system <NUM> may cooperate with the other components of the flight control system <NUM> to control operation of the aerial vehicle <NUM> and navigate the vehicle along an intended path.

The gyroscope <NUM> may be a device configured to detect rotation of the aerial vehicle <NUM> or a surface to which the gyroscope <NUM> is coupled (e.g., a portion of the DVE-resistant LIDAR system <NUM>). The gyroscope <NUM> may be integral with the aerial vehicle <NUM> or it may be disposed outside of the aerial vehicle <NUM>. The gyroscope <NUM> may include any gyroscope or variations thereof (e.g., gyrostat, microelectromechanical systems ("MEMS"), fiber-optic gyroscope, vibrating-structure gyroscope, dynamically tuned gyroscope, and the like) known in the art or that will become known in the art. The gyroscope <NUM> may cooperate with the other components of the flight control system <NUM> to control operation of the aerial vehicle <NUM> and navigate the vehicle along an intended path.

The accelerometer <NUM> may be any device configured to detect a linear motion of the aerial vehicle <NUM>. The accelerometer <NUM> may be integral with the aerial vehicle <NUM> or it may be disposed inside or outside of the aerial vehicle <NUM>. The accelerometer <NUM> may include may include any accelerometer known in the art (e.g., capacitive, resistive, spring-mass base, direct current ("DC") response, electromechanical servo, laser, magnetic induction, piezoelectric, optical, low frequency, pendulous integrating gyroscopic accelerometer, resonance, strain gauge, surface acoustic wave, MEMS, thermal, vacuum diode, and the like) or that will become known in the art. The accelerometer <NUM> may cooperate with the other components of the flight control system <NUM> to control operation of the aerial vehicle <NUM> and navigate the vehicle along an intended path.

Other sensors (or sensor systems) <NUM> may also be similarly employed. For example, the aerial vehicle <NUM> (or the flight control system <NUM>, DVE-resistant LIDAR system <NUM>, etc.) may employ infrared sensors, RADAR (i.e., RAdio Detection And Ranging) sensors, and so forth.

The flight control processor <NUM> may be coupled in a communicating relationship with the flight controller <NUM>, the aerial vehicle <NUM>, the flight control system <NUM>, the steering mechanism <NUM>, and the other various other components, systems, and subsystems described herein, such as the DSP <NUM> of the DVE-resistant LIDAR system <NUM>. The flight control processor <NUM> may be an internal processor of the aerial vehicle <NUM> or the flight control system <NUM>, an additional processor to support the various functions contemplated herein, a processor of a desktop computer or the like, locally or remotely coupled to the aerial vehicle <NUM>, and the flight control system <NUM>, a server or other processor coupled to the aerial vehicle <NUM> and the flight control system <NUM> through a data network, or any other processor or processing circuitry. In general, the flight control processor <NUM> may be configured to control operation of the aerial vehicle <NUM> or the flight control system <NUM> and perform various processing and calculation functions to support navigation. The flight control processor <NUM> may include a number of different processors cooperating to perform the steps described herein, such as where an internal processor of the aerial vehicle <NUM> controls operation of the aerial vehicle <NUM> while a processor in the housing preprocesses optical and echolocation data.

The flight control processor <NUM> may be configured to determine or revise a navigational path for the aerial vehicle <NUM> to a location based upon a variety of inputs including, e.g., position information, movement information, data from the DVE-resistant LIDAR system <NUM>, and so forth, which may be variously based on data from the GPS system <NUM>, the map system <NUM>, the gyroscope <NUM>, the accelerometer <NUM>, and any other navigation inputs, as well as an optical system and the echolocation system, which may provide information on obstacles in an environment around the aerial vehicle <NUM>. An initial path may be determined, for example, based solely on positional information provided by the GPS system <NUM>, with in-flight adjustments based on movements detected by the gyroscope <NUM>, accelerometer <NUM>, and the like. The flight control processor <NUM> may also be configured to utilize an optical navigation system, where the processor is configured to identify a visible obstacle within the FOV of an optical system; for example, using optical flow to process a sequence of images and to preempt the GPS system <NUM> to navigate the aerial vehicle <NUM> around visible obstacles and toward the location. The flight control processor <NUM> may be further configured to identify an obstacle within the FOV of the DVE-resistant LIDAR system <NUM> or ISR payload <NUM>, usually within a line of flight of the vehicle, and further configured to preempt the GPS system <NUM> and the optical navigation system to execute a responsive maneuver that directs the aerial vehicle <NUM> around the obstacle and returns the aerial vehicle <NUM> to a previous course toward the location.

The flight controller <NUM> may be operable to control components of the aerial vehicle <NUM> and the flight control system <NUM>, such as the steering mechanism <NUM>. The flight controller <NUM> may be electrically or otherwise coupled in a communicating relationship with the flight control processor <NUM>, the aerial vehicle <NUM>, the flight control system <NUM>, the steering mechanism <NUM>, and the other various components of the devices and systems described herein. The flight controller <NUM> may include any combination of software and/or processing circuitry suitable for controlling the various components of the aerial vehicle <NUM> and the flight control system <NUM> described herein, including, without limitation, microprocessors, microcontrollers, application-specific integrated circuits, programmable gate arrays, and any other digital and/or analog components, as well as combinations of the foregoing, along with inputs and outputs for transceiving control signals, drive signals, power signals, sensor signals, and so forth. In one aspect, this may include circuitry directly and physically associated with the aerial vehicle <NUM> and the flight control system <NUM>, such as an on-board processor. In another aspect, this may be a processor, such as the flight control processor <NUM> described herein, which may be associated with a personal computer or other computing device coupled to the aerial vehicle <NUM> and the flight control system <NUM>, e.g., through a wired or wireless connection. Similarly, various functions described herein may be allocated among an on-board processor for the aerial vehicle <NUM>, the flight control system <NUM>, and a separate computer. All such computing devices and environments are intended to fall within the meaning of the term "controller" or "processor" as used herein, unless a different meaning is explicitly provided or otherwise clear from the context.

The memory devices <NUM>, <NUM> may include local memory or a remote storage device that stores a log of data for the flight control system <NUM> and/or the DVE-resistant LIDAR system <NUM>, including, without limitation, the location of sensed obstacles, maps, images, orientations, speeds, navigational paths, steering specifications, GPS coordinates, sensor readings, and the like. The memory devices <NUM>, <NUM> may also, or instead, store sensor data from the ISR payload <NUM> and/or the DVE-resistant LIDAR system <NUM>, related metadata, and the like. Data stored in the memory device <NUM> may be accessed by the flight control processor <NUM>, the flight controller <NUM>, the DVE-resistant LIDAR system <NUM>, a remote processing resource, and the like.

In operation, the DVE-resistant LIDAR system <NUM> may transmit a signal while operating in the DVE that returns primarily backscatter from the DVE media <NUM>. This return is used to phase conjugate the SLM <NUM> to tune out the interfering backscatter from the media. As the target <NUM> comes within range, the backscatter characteristics of the target <NUM> will appear in the received signal, but the backscatter of the target <NUM> will have different properties than the previously detected media of the DVE. The system will continue to phase conjugate the SLM <NUM> with the medial backscatter signal to maximize the signal of the target <NUM>, thus allowing detection of the target <NUM> backscatter at a range greater than is possible with other current techniques. If no target <NUM> is detected even at the optimized SLM modulation, the LIDAR probes to the next increment of range and repeats, until either the target <NUM> is acquired or the limits of the LIDAR of the described system is detected.

Initial DVE backscatter phase conjugate corrections may be pre-loaded in the system (e.g., stored to memory device <NUM>), which may comprise separate initial SLM corrections for different common DVE conditions such as rain, fog, smoke, or dust. These SLM corrections may incorporate a pre-learned database of different operational conditions using convolutional neural networks which model the optical transmission matrix. DVE backscatter corrections can be sampled in real time by measuring backscatter to a predetermined range that is known to be free of the target <NUM>. The DVE backscatter correction may be iterated from near ranges to distant ranges until a change in the property of the backscatter is detected that indicates that the DVE media <NUM> has changed. In certain aspects, the DVE backscatter correction sampling is bounded to space that is known from a prior terrain map to contain free space.

<FIG> shows a flowchart of an example method of operation <NUM> for the DVE-resistant LIDAR system <NUM>. The method <NUM> iterates a search, starting with the minimum range at which the DVE media <NUM> could be meaningfully correlated and a conjugate generated. The DVE-resistant LIDAR system <NUM> is initialized at step <NUM> to starting parameters for normal, non-DVE operation as in a conventional LIDAR. Then, the DVE-resistant LIDAR system <NUM> checks, via DSP <NUM>, to see if DVE mode is selected at step <NUM>. If not, conventional operation continues as in steps <NUM> and <NUM>. However, if DVE mode is selected or a range is not acquired in step <NUM>, the DVE-resistant LIDAR system <NUM> will attempt to acquire a range in DVE mode by first, looking for a phase conjugate that generates a return at the minimum effective range of the system in step <NUM>. If a conjugation is successful at that distance as tested at step <NUM>, the system will increment the range and attempt conjugation again in step <NUM>. When conjugation fails, that determines the maximum depth of penetration achievable in the current DVE. If the scan fails at <NUM> and it is the first pass <NUM>, then the system is unable to locate a target <NUM> at all and the method reverts to the initial conditions, at which point the method of operation <NUM> may report failure and return to initial condition at step <NUM>. Otherwise, the last successful conjugation distance is reported as the current effective range of the LIDAR at step <NUM>. The method <NUM> then scans for a reflected return <NUM> from target <NUM> within that effective range envelope in step <NUM>. If a target is found at step <NUM>, the DVE-resistant LIDAR system <NUM> reports that range out at step <NUM>. If no target is found, the process can repeat with step <NUM> for as long as the decorrelation window for the DVE remains open. However, decorrelation times are expected to be short relative to the need for a new range update, so for moving vehicles the process will generally repeat with step <NUM> at the expiration of a decorrelation window.

With reference to <FIG>, the DVE-resistant LIDAR system <NUM> may determine a state estimate of the aerial vehicle at step <NUM> via, for example, a processor (e.g., flight control processor <NUM>, DSP <NUM>, etc.). For example, the processor may determine the position and/or pose of the aerial vehicle <NUM> using one or more factors <NUM>. The one or more factors <NUM> may include, for example GPS data, IMU data, point clouds, data related to the scatterers in the DVE media <NUM>, etc. The factors <NUM> may be received from, for example, the flight control system <NUM>, ISR payload <NUM>, etc. At step <NUM>, the scattering matrix is updated using, for example, scattering layer unpeeling (e.g., of the DVE media <NUM>). At step <NUM>, the phase conjugation is updated using, for example, Fienup reconstruction, machine learning, etc. At step <NUM>, the point cloud measurement is used to update the SLM <NUM>. The updated point cloud measurement may be stored at step <NUM> for future use.

The DVE-resistant LIDAR system <NUM> may use phase retrieval algorithms and/or learning tomography. <FIG> illustrates an example block diagram of performing a Fienup reconstruction. For example, Fienup's phase retrieval is the process of algorithmically finding solutions to the phase problem. Given a complex signal F(k), of amplitude |F(k)|, and phase ψ (k): <MAT> where x is an M-dimensional spatial coordinate and k is an M-dimensional spatial frequency coordinate, phase retrieval consists in finding the phase that for a measured amplitude satisfies a set of constraints. In another example, learning tomography is used to generate a reconstruction model based on beam propagation method that takes multiple scattering into account.

The DVE-resistant LIDAR system <NUM> is particularly useful for autonomous landing of VTOL aerial vehicles in DVEs where the exact landing location is approximately known (but not precisely known) and higher energy methods of scanning for a non-visible surface, such as radar, are not desirable, for example because the emissions from a microwave landing system could be detected and attacked in a battlefield environment. An autonomous vertical lift vehicle may use the DVE-resistant LIDAR system <NUM> to fly to a roughly designated landing point, and then begin descending into the DVE using the LIDAR to detect the ground. Even in the presence of, for example, battlefield smoke, the DVE-resistant LIDAR system <NUM> allows the vehicle to detect the ground accurately at a sufficiently large distance that the vehicle can descend at a rate faster than it would if the vehicle had a higher uncertainty as to the point where the landing would take place. Higher descent rates, or descent when conventional optical approach guidance is not available at all, gives a vehicle equipped with the DVE-resistant LIDAR system <NUM> a capability and survivability advantage.

Claim 1:
A LIDAR system (<NUM>) for an aerial vehicle (<NUM>) operating in a degraded visual environment (DVE), the LIDAR system (<NUM>) comprising:
a laser source (<NUM>) configured to emit a coherent light beam;
a spatial light modulator to modulate said coherent light beam, wherein the spatial light modulator is configured to phase conjugate an interference pattern of a DVE medium (<NUM>, <NUM>) that is positioned between said spatial light modulator and a target (<NUM>);
an optical lens (<NUM>) to filter said coherent light beam from the spatial light modulator, wherein the optical lens (<NUM>) is configured to direct the coherent light beam toward the target (<NUM>), wherein the coherent light beam reflects off of the DVE medium (<NUM>, <NUM>) to yield scattered photons and reflects off of the target (<NUM>) to yield reflected photons;
a second optical lens (<NUM>) to collect the scattered photons and the reflected photons; and
a detector array to detect the scattered photons and the reflected photons,
wherein the LIDAR system (<NUM>) is configured to iteratively scan a plurality of conjugates to identify a current scattering property of said DVE medium (<NUM>, <NUM>),
wherein the step for iteratively scanning the plurality of conjugates uses a Fienup reconstruction technique, and
wherein the LIDAR system (<NUM>) is configured to probe at successively longer presumed ranges until a predetermined time for a scan exceeds a decorrelation time of said DVE medium (<NUM>, <NUM>) at a presumed distance.