Ocean three-dimensional detection method and system based on unmanned aerial vehicle fusion microwave and laser

Abstract

The present application relates to the technical field of ocean observation and remote sensing data processing, in particular to a kind of ocean three-dimensional detection method and system based on unmanned aerial vehicle fusion microwave and laser, comprising: target sea area identification and task planning;Based on satellite altimeter sea surface height anomaly data, determine target area and unmanned aerial vehicle route;Multi-sensor synchronous acquisition synchronous detection data;Synchronous detection data driven ocean structure joint inversion: microwave and laser synchronous detection result co-registration fusion and ocean quasi-three-dimensional structure construction.The present application takes microwave and laser synchronous detection result as data basis, after sea surface height anomaly calculation, internal thermal structure inversion, chlorophyll anomaly profile inversion, realizes the mutual corresponding ocean quasi-three-dimensional detection between sea surface dynamic signal, upper ocean internal thermal structure and water vertical parameter.

Description

Technical Field

[0001] This invention relates to the field of marine observation and remote sensing data processing technology, and in particular to a method and system for three-dimensional marine detection based on unmanned aerial vehicles (UAVs) that integrates microwave and laser technologies. Background Technology

[0002] Upper ocean processes are characterized by significant multi-scale and transient nature. Traditional in-situ observation methods, such as shipborne profiling and fixed-point mooring, can provide high-precision vertical information, but their coverage is limited and sampling cycles are long, making it difficult to continuously characterize regional-scale dynamic and ecological structures under the same spatiotemporal reference. Satellite remote sensing can provide large-scale sea surface observations, but it is usually difficult to simultaneously resolve the internal vertical structure of water bodies, and the sampling time difference and spatial resolution differences between multi-source products can easily introduce aliasing errors.

[0003] In marine areas dominated by structures such as eddies and fronts, sea surface height anomalies are often closely coupled with the morphology of the upper ocean thermocline and the bio-optical structure of the water body. However, in existing observation systems, there is a lack of unified spatiotemporal constraints between sea surface observations and water body profile observations. Subsequent processing often relies on post-hoc registration and interpolation fusion, which is insufficient to meet the requirements of collaborative observations with strict co-tracking, simultaneity, and shared geographic reference. Therefore, there is an urgent need for a method and system for three-dimensional ocean exploration based on unmanned aerial vehicles (UAVs) that integrates microwave and laser technologies. This system would be used to simultaneously acquire sea surface dynamic signals, vertical parameter profiles of the water body, and the internal thermal structure of the upper ocean under a unified time reference and geographic reference system, thereby reducing spatiotemporal mismatch and improving the ability to characterize the three-dimensional structure of the ocean. Summary of the Invention

[0004] This invention provides a method and system for three-dimensional ocean detection based on unmanned aerial vehicles (UAVs) that integrates microwave and laser technologies, in order to solve the above-mentioned problems.

[0005] This invention provides a method for three-dimensional ocean detection based on unmanned aerial vehicles (UAVs) fusing microwave and laser technologies, characterized by the following steps: Step 1: Target Sea Area Identification and Mission Planning By combining the type of ocean process to be observed, the endurance of the UAV, the flight airspace conditions, and the needs of on-site collaborative observation, the target sea area is identified and the mission is planned, and mission execution parameters and candidate observation schemes are formed. Step 2: Based on the sea surface height anomaly data from the satellite altimeter, determine the target area and the UAV flight path: Based on the sea surface height anomaly background field fused from multi-source satellite radar altimeters, the target sea area is identified, the target region is determined, and UAV flight survey lines are generated. Step 3: Simultaneously acquire synchronous detection data from multiple sensors; Using a drone equipped with a microwave altimeter and marine lidar, and with a unified time reference, unified navigation and attitude information, and a unified geographic reference system provided by a global navigation satellite system / inertial navigation system, synchronous detection data is acquired along the flight survey line. The synchronous detection data includes microwave echo sequences, laser echo waveforms, and corresponding positioning attitude data. Step 4: Joint inversion of ocean structure driven by synchronous detection data: Based on synchronous detection data, the sea surface dynamic field, internal thermal structure and water body parameter profiles were jointly inverted to obtain the sea surface height anomaly SLA along the track, the vertical thermal structure of the upper ocean and the vertical profile of chlorophyll anomaly, respectively. Step 5: Co-registration and fusion of microwave and laser synchronous detection results and construction of quasi-3D ocean structure: Constrained by the unified time reference and unified geographic reference system established in step three, the sea surface height anomaly SLA, upper ocean vertical thermal structure, and chlorophyll anomaly vertical profile obtained in step four are mapped to the unified track coordinate system to form a quasi-three-dimensional ocean exploration product with the same track, time, and geographic reference, and the ocean quasi-three-dimensional exploration results are output.

[0006] As a preferred technical solution, step four involves the joint inversion of the sea surface dynamic field, internal thermal structure, and water parameter profiles as follows: Step 41, Solving for sea surface height anomalies using microwave altimetry: Pulse compression and waveform retracking were performed on the microwave echo sequence to obtain the one-way geometric slant range from the antenna phase center to the instantaneous sea surface. By combining the high-frequency trajectory and attitude information obtained from GNSS / INS calculations, motion compensation and lever correction are performed to obtain the sea surface height sequence (SSH) along the track. After removing the mean sea level and applying geophysical corrections, the sea surface height anomaly (SLA) along the track is obtained. The geophysical corrections include tidal corrections, solid earth tidal corrections, polar tidal corrections, anti-pressure corrections, and system residual bias corrections. Step 42, Internal thermal structure inversion: Using the sea surface height anomaly (SLA) along the navigation track as input, and combining spatiotemporal parameters such as latitude and time index, the sea surface height change signal is inverted based on a pre-trained mapping model to obtain the vertical thermal structure of the upper ocean. Step 43, Laser Profile Inversion: The laser echo waveform is preprocessed and converted from the time domain to the depth domain to obtain the backscattering profile of the water body. Based on the regional inversion framework or the parameter optimization inversion framework, a depth-resolved vertical profile of chlorophyll anomalies is obtained.

[0007] As a preferred technical solution, in step 41, the slope distance The ranging model is represented as: (1) in, At the speed of light, The sampling start time, For system hardware latency, The leading edge feature point index determined by the re-tracking algorithm, The number of sampling points in the distance direction. This represents the time resolution after pulse compression. The expression for the sea surface altitude sequence SSH along the track is: (2) Where H is the height of the UAV relative to the reference ellipsoid. The antenna's angle from the nadir, determined by attitude information; The expression for the sea surface height anomaly (SLA) along the track is: (3) MSS stands for Mean Sea Level Model. This is a geophysical correction.

[0008] As a preferred technical solution, perform odd-even sampling differential quality assessment on the sea surface altitude sequence along the navigation track: The sequence of sea surface altitudes along a flight path in a certain frequency band is defined as follows: Divide it into odd sampled subsequences And even sampling subsequence Then the difference sequence is: (4) Perform linear fitting on the difference sequence: (5) The residual sequence is then: (6)

[0009] If the standard deviation of the residual sequence is The effective altimetry accuracy of the original sea surface height sequence along the navigation track is: (7)

[0010] The above evaluation results of the odd-even sampling differential accuracy are used to determine the quality of microwave altimetry data and to mark the output confidence level.

[0011] As a preferred technical solution, in step 42, the pre-trained mapping model is a neural network model, and its output vector is represented as follows: (8) in, This represents the temperature value or temperature anomaly value of the i-th depth layer; During model training, the network parameters are optimized by minimizing the mean square error between the predicted profile and the reference profile. (9) in, For reference temperature profile, N represents the temperature profile predicted by the model, and N is the number of training samples.

[0012] As a preferred technical solution, in step 43, the laser received signal satisfies the following lidar equation: (10)

[0013] in, Let A be the echo signal at depth z, and A be the system calibration constant. The volume scattering function is 180°. This is the diffuse decay coefficient; The effective detection depth of the laser is the maximum effective depth when the signal-to-noise ratio of the water echo signal drops to a preset threshold; a signal-to-noise ratio of 1 is used as the effective detection depth threshold.

[0014] As a preferred technical solution, in step three, the microwave altimeter is a Ka / Ku dual-frequency microwave altimeter, and the marine lidar is a blue-green dual-wavelength marine lidar with wavelengths of 486 nm and 532 nm, respectively.

[0015] As a preferred technical solution, the quasi-three-dimensional ocean detection results are expressed as follows: (11)

[0016] Where s is the coordinate along the track, SLA(s) is the sea surface height anomaly along the track, T(s,z) is the internal thermal structure profile, P(s,z) is the vertical profile of chlorophyll anomaly, and Q(s,z) is the quasi-three-dimensional ocean exploration result.

[0017] This invention also provides a three-dimensional ocean detection system based on unmanned aerial vehicles (UAVs) that integrates microwave and laser technologies, applied to the above-mentioned method, comprising: The mission planning module is used to identify target sea areas based on sea surface height anomaly data fused from multi-source satellite radar altimeters, generate UAV flight survey lines, and output flight altitude, flight speed, heading, survey line spacing, and collaborative on-site station parameters. The data acquisition module includes a microwave altimeter unit, a marine lidar unit, and a GNSS / INS navigation and attitude determination unit. It is used to simultaneously acquire microwave echo sequences, laser echo waveforms, and corresponding positioning and attitude data during the flight of the UAV along the flight survey line set by the mission planning module. The microwave altimeter processing module is used to process the microwave echo sequence acquired by the microwave altimeter radar altimeter unit in the data acquisition module to obtain the change signal of sea surface altitude anomaly (SLA) along the track. The internal thermal structure inversion module uses a pre-trained mapping model to invert the vertical thermal structure of the upper ocean based on the change signal of the sea surface height anomaly (SLA) along the track. The laser profile processing module is used to preprocess, perform depth domain conversion, and invert water parameters on the laser echo waveform acquired by the data acquisition module to generate a vertical profile of chlorophyll anomalies along the flight path. The fusion and reconstruction module is used to co-register and fuse the surface height anomaly (SLA), upper ocean vertical thermal structure, and chlorophyll anomaly vertical profile along the track under a unified time reference and geographic reference system to generate quasi-three-dimensional ocean exploration results. The data storage and display module is used to store and display the quasi-three-dimensional marine exploration results generated by the fusion reconstruction module.

[0018] As a preferred technical solution, the data acquisition module further includes an auxiliary sensor unit, which includes an infrared imaging unit and an optical polarization imaging unit, used to identify sea surface temperature texture, specular reflection area, white waves, cloud and rain obscured area or strong glare area. The microwave altimetry processing module is equipped with a quality control unit. The quality control unit is used to perform abnormal segment removal based on GNSS / INS attitude thresholds, system delay and transmit power stability monitoring based on internal loop calibration, abnormal echo screening based on microwave echo waveform morphology, and cross-validation based on satellite and / or field observations on the original microwave echo sequence and corresponding GNSS / INS attitude data. Combined with the evaluation results of odd-even sampling differential accuracy, the quality control unit outputs quality labels or confidence information for the microwave altimetry data.

[0019] This invention provides a method and system for three-dimensional ocean detection based on unmanned aerial vehicles (UAVs) fusing microwave and laser technologies, which has the following beneficial effects: I. Target sea area identification, route determination, and dynamic updating based on the background field of sea surface height anomalies from satellite altimeters can improve the matching degree between observation tasks and target ocean processes, and reduce spatiotemporal mismatch errors caused by target movement and evolution.

[0020] Second, by working together with microwave altimeter, marine lidar and GNSS / INS navigation and attitude determination system, sea surface dynamic signals and water body vertical echo information can be acquired synchronously under a unified time reference and a unified geographic reference system, thereby improving the correspondence and fusion of multi-source detection data.

[0021] Third, through joint inversion of ocean structure driven by synchronous detection data, it is possible to obtain vertical profiles of sea surface height anomalies (SLA), internal thermal structure of the upper ocean, and chlorophyll anomalies along the track, and form quasi-three-dimensional ocean detection results under a unified track coordinate system, thereby improving the quasi-three-dimensional detection capability of the upper ocean structure.

[0022] Fourth, by setting up a quality control unit within the microwave altimetry processing module, it is possible to perform abnormal segment removal, calibration stability monitoring, abnormal echo screening, and cross-validation on the original microwave echo sequence and corresponding attitude data, thereby improving the reliability of the sea surface height anomaly calculation results.

[0023] V. This invention is applicable to the refined observation of highly dynamic sea areas such as eddies and fronts, and can provide technical support for the fusion remote sensing observation of ocean dynamic structure, water body vertical parameter structure and upper ocean internal thermal structure. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating the ocean three-dimensional detection method based on unmanned aerial vehicles (UAVs) integrating microwave and laser technologies, as described in this invention. Figure 2 This is a schematic diagram of the ocean quasi-three-dimensional detection and collaborative observation strategy of the present invention; Figure 3 This is a flowchart of the collaborative observation process for quasi-three-dimensional marine exploration according to the present invention; Figure 4 This is a schematic diagram showing the flight path of the UAV and the distribution of the shipborne on-site stations according to the present invention; Figure 5 This is a diagram showing the absolute ranging calibration results of the UAV system of the present invention; Figure 6 This is a comparison chart of the accuracy of the fusion product of the sea surface height anomaly along the flight path and the Multi-Source Satellite Altimeter Data Unified Processing System (DUACS) of this invention; Figure 7 This is a comparison chart of the accuracy of the sea surface height anomaly along the flight path and the wide-format product of the Surface Water and Ocean Topography Satellite (SWOT). Figure 8 This is a diagram showing the vertical profile results of chlorophyll anomalies along the flight path obtained by the airborne marine lidar of this invention. Figure 9 This is a quasi-three-dimensional structural diagram. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0027] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0028] The embodiments of the present invention will now be described in further detail with reference to the accompanying drawings.

[0029] Example 1: See Figures 1 to 3 This invention provides a method for three-dimensional ocean detection based on unmanned aerial vehicles (UAVs) fusing microwave and laser technologies, comprising the following steps: Step 1: Target sea area identification and mission planning; Before the mission is carried out, the target sea area is identified and the mission is planned by taking into account the type of ocean process to be observed, the endurance of the UAV, the airspace conditions, flight altitude, flight speed, survey line spacing, heading and on-site collaborative observation requirements, so as to form mission execution parameters and candidate observation schemes.

[0030] Step 2: Based on the sea surface height anomaly data from the satellite altimeter, determine the target area and the UAV flight path; The target sea area is screened based on the sea surface height anomaly background field fused from multi-source satellite radar altimeters to identify significant dynamic structures, determine the target region, and generate UAV flight survey lines. The UAV flight path direction can be determined based on the spatial morphology, gradient distribution, and evolution trend of the sea surface height anomaly, enabling the UAV to conduct continuous traversal observations along the key axes of the target structure. Before each flight mission, the target area boundary, UAV flight survey lines, and collaborative field observation station positions are updated based on the latest acquired sea surface height anomaly background field to reduce spatiotemporal mismatch errors caused by the translation and evolution of oceanic processes.

[0031] Step 3: Simultaneously acquire synchronous detection data from multiple sensors; By utilizing a large UAV equipped with a microwave altimeter and a marine lidar, and by providing a unified time reference, unified navigation and attitude information, and a unified geographic reference system through a global navigation satellite system / inertial navigation system, synchronous detection data is acquired along the flight survey line. The synchronous detection data includes microwave echo sequences, laser echo waveforms, and corresponding positioning and attitude data, thereby achieving synchronous sampling of sea surface dynamic signals and water body vertical echo signals under the same flight path.

[0032] The microwave altimeter is a Ka / Ku dual-frequency microwave altimeter, and the marine lidar is a blue-green dual-wavelength marine lidar with wavelengths of 486 nm and 532 nm, respectively. Furthermore, the microwave altimeter antenna is mounted in the front region of the UAV, and the marine lidar transceiver head is mounted in the rear region of the UAV to reduce platform jitter, antenna pointing errors, and electromagnetic coupling interference.

[0033] Step 4: Joint inversion of ocean structure driven by synchronous detection data; This step uses the synchronous detection data obtained in step three, namely microwave echo, laser echo and corresponding positioning attitude data, as the basis to jointly invert the sea surface dynamic field, internal thermal structure and water parameter profile.

[0034] Step 41: Solving Sea Surface Height Anomalies via Microwave Altimetry

[0035] Pulse compression and waveform retracking are performed on the microwave echo sequence to obtain the one-way geometric slant range from the antenna phase center to the instantaneous sea surface; its ranging model can be expressed as: (1) in, At the speed of light, The sampling start time, For system hardware latency, The leading edge feature point index determined by the re-tracking algorithm, The number of sampling points in the distance direction. This represents the time resolution after pulse compression.

[0036] In obtaining the slope distance Then, by combining the high-frequency trajectory and attitude information obtained from GNSS / INS calculations, motion compensation and lever correction are performed to obtain the sea surface height SSH along the track, which is expressed as: (2) Where H is the height of the UAV relative to the reference ellipsoid. The antenna's angle from the nadir, determined by attitude information. Further, after removing the mean sea level and applying geophysical corrections, the sea level height anomaly SLA along the track is obtained: (3) MSS stands for Mean Sea Level Model. These are geophysical correction terms. The geophysical correction terms include at least tidal correction, solid earth tide correction, polar tide correction, anti-pressure correction, and system residual bias correction. If necessary, low-pass filtering and slowly varying component removal can be applied to the sea surface height sequence along the track or the sea surface height anomaly sequence to suppress high-frequency disturbances and long-wave drift, preserving effective scale signals related to the target ocean processes.

[0037] To quantify the effective accuracy of microwave altimetry results, an odd-even sampling differential quality assessment can be performed on the sea surface altitude sequence along the navigation track: Let the sea surface altitude sequence along the navigation track in a certain frequency band be... Divide it into odd sampled subsequences And even sampling subsequence Then the difference sequence is: (4)

[0038] Perform linear fitting on the difference sequence: (5)

[0039] The residual sequence is then: (6)

[0040] If the standard deviation of the residual sequence is The effective altimetry accuracy of the original sea surface height sequence along the navigation track is: (7)

[0041] The above evaluation results of the odd-even sampling differential accuracy are used to determine the quality of microwave altimetry data and to mark the output confidence level.

[0042] To verify the operational stability and ranging accuracy of the airborne microwave altimetry subsystem in the UAV microwave and laser fusion marine 3D exploration system of this invention, internal calibration records show that the equivalent time delay of the signal sequence is stably concentrated around 182.225 meters in the Ku band and 182.152 meters in the Ka band, while the transmission power is stable around 48.44 dB in the Ku band and 41.34 dB in the Ka band. The consistency between the inverted sea surface height and the mean sea surface reference during offshore flight indicates that the relative altimetry accuracy can reach 3.5 cm in the Ka band and 4.3 cm in the Ku band.

[0043] Step 42: Internal thermal structure inversion

[0044] Using the sea surface height anomaly (SLA) along the navigation track obtained in step 41 as input, and combining spatiotemporal parameters such as latitude and time index, the sea surface height change signal is inverted based on a pre-trained mapping model to obtain the vertical thermal structure of the upper ocean. This step is used to establish the mapping relationship between the sea surface dynamic signal and the internal thermal structure of the upper ocean, and to generate a thermal structure profile with depth resolution. The pre-trained mapping model is a neural network model, and its output vector can be represented as:

[0045] (8)

[0046] in, This represents the temperature value or temperature anomaly value of the i-th depth layer.

[0047] During model training, the network parameters are optimized by minimizing the mean square error between the predicted profile and the reference profile.

[0048] (9)

[0049] in, For reference temperature profile, N represents the temperature profile predicted by the model, and N is the number of training samples.

[0050] Step 43: Laser profile inversion

[0051] The laser echo waveform is preprocessed, including at least sea surface echo detection and alignment, removal of specular reflection components from the sea surface, background noise subtraction, and removal of echoes affected by clouds and rain. The preprocessed waveform is then converted from the time domain to the depth domain to obtain a water backscattering profile. Based on a regional inversion framework or a parameter optimization inversion framework, a depth-resolved chlorophyll anomaly vertical profile is further obtained. The laser received signal satisfies the following lidar equation:

[0052] (10)

[0053] in, Let A be the echo signal at depth z, and A be the system calibration constant. The volume scattering function is 180°. This is the diffuse decay coefficient.

[0054] Based on the above relationships, chlorophyll concentration profiles, backscattering profiles, or other water body parameter profiles can be further retrieved.

[0055] Furthermore, the effective detection depth is defined as the maximum effective depth corresponding to the point where the signal-to-noise ratio of the water echo signal drops to a preset threshold. This invention uses a signal-to-noise ratio of 1 as the effective detection depth threshold.

[0056] Step 5: Co-registration and fusion of microwave and laser synchronous detection results and construction of quasi-three-dimensional marine structure; Constrained by the unified time reference and unified geographic reference system established in step three, the sea surface height anomaly (SLA), upper ocean vertical thermal structure, and chlorophyll anomaly vertical profile obtained in step four are mapped to the unified track coordinate system to form a quasi-three-dimensional ocean exploration product with the same track, time, and geographic reference, and the ocean quasi-three-dimensional exploration results are output.

[0057] The results of the quasi-three-dimensional ocean exploration can be expressed as follows:

[0058] (11)

[0059] Where s is the coordinate along the track, SLA(s) is the sea surface height anomaly along the track, T(s,z) is the internal thermal structure profile, P(s,z) is the vertical profile of chlorophyll anomaly, and Q(s,z) is the quasi-three-dimensional ocean exploration result.

[0060] The quasi-three-dimensional detection product of the present invention includes a sea surface height anomaly (SLA) along the track, a corresponding upper ocean internal thermal structure profile, and a co-registered chlorophyll anomaly vertical profile, for characterizing the quasi-three-dimensional structure of the upper ocean water.

[0061] Example 2: This invention also provides a marine three-dimensional detection system based on unmanned aerial vehicles (UAVs) fusing microwave and laser technologies, used to implement the aforementioned marine three-dimensional detection method based on UAVs fusing microwave and laser technologies. The system includes: a mission planning module, a data acquisition module, a microwave altimetry processing module, an internal thermal structure inversion module, a laser profile processing module, a fusion reconstruction module, and a data storage and display module.

[0062] The task planning module is used to identify target sea areas based on sea surface height anomaly data fused from multi-source satellite radar altimeters, generate UAV flight survey lines, and output flight altitude, flight speed, heading, survey line spacing, and collaborative on-site station parameters. The data acquisition module includes a microwave altimeter unit, a marine lidar unit, and a GNSS / INS navigation and attitude determination unit, which are used to simultaneously acquire microwave echo sequences, laser echo waveforms, and corresponding positioning attitude data during the flight of the UAV along the flight survey line set by the mission planning module. The microwave altimeter processing module is used to process the microwave echo sequence acquired by the microwave altimeter radar altimeter unit in the data acquisition module to obtain the change signal of sea surface altitude anomaly SLA along the track. The internal thermal structure inversion module is used to invert the vertical thermal structure of the upper ocean using a pre-trained mapping model based on the change signal of the sea surface height anomaly (SLA) along the navigation track. The laser profile processing module is used to preprocess, perform depth domain conversion, and invert water parameters on the laser echo waveform acquired by the data acquisition module to generate a vertical profile of chlorophyll anomalies along the flight path. The fusion and reconstruction module is used to perform co-registration and fusion of surface height anomalies (SLA), upper ocean vertical thermal structure, and chlorophyll anomaly vertical profiles along the navigation track under a unified time reference and geographic reference system to generate quasi-three-dimensional ocean detection results. The data storage and display module is used to store and display the quasi-three-dimensional marine exploration results generated by the fusion reconstruction module.

[0063] The data acquisition module also includes an auxiliary sensor unit, which includes an infrared imaging unit and an optical polarization imaging unit, used to identify sea surface temperature texture, specular reflection areas, white waves, cloud and rain obscured areas, or strong glare areas, so as to enhance the robustness of sea surface detection and data quality control.

[0064] The microwave altimeter processing module includes a quality control unit. This quality control unit performs the following operations on the original microwave echo sequence and corresponding GNSS / INS attitude data: anomaly segment removal based on GNSS / INS attitude thresholds; system delay and transmit power stability monitoring based on internal loopback calibration; anomaly echo screening based on microwave echo waveform morphology; and cross-validation based on satellite and / or field observations. Combined with the evaluation results of odd / even sampling differential accuracy, it outputs quality markers or confidence information for the microwave altimeter data to improve the reliability of the sea surface height anomaly calculation results.

[0065] like Figure 3 As shown, this embodiment employs a collaborative observation framework of "satellite background identification—mission control—cooperative observation—quasi-3D structure reconstruction" across air, space, and sea. First, target vortex regions are identified based on sea surface height anomaly data fused from satellite radar altimeters, and vortex location and boundary information are extracted. Then, the mission control center determines the location of in-situ observation stations, dynamically adjusts observation routes, and organizes collaborative observation. During the collaborative observation phase, sea surface dynamic signals and internal water structure information are acquired through multi-source observation methods, including satellite altimeters, UAV-borne microwave altimeter altimeters, marine lidar, shipborne marine lidar, and wave energy profiling buoys. These are then used to form a quasi-3D ocean structure characterization result under a unified spatiotemporal reference system. The accompanying figure illustrates that this invention not only enables airborne collaborative observation but also forms a joint verification link with satellite and field observations, thereby improving the reliability and completeness of the observation results.

[0066] like Figure 4As shown, a joint observation experiment was conducted in a selected vortex-like sea area. The UAV performed multiple flights along the target vortex axis, obtaining continuous track profiles spanning cyclones and anticyclones. Simultaneously, in-situ stations were deployed near the UAV tracks to acquire hydrological and biological profile data concurrently. The background field in the figure is a multi-source satellite altimeter fusion sea surface height anomaly field. The UAV tracks and in-situ stations respectively cover different dynamic regions of the dipole vortex, providing a unified observational basis for subsequent sea surface height anomaly inversion, water parameter profile inversion, and their co-registration and fusion. This figure illustrates that the present invention can perform route planning and collaborative deployment of in-situ stations around rapidly evolving marine dynamic targets, thereby reducing spatiotemporal mismatch errors caused by target translation.

[0067] like Figure 5 As shown, comparing the sea surface height obtained along the flight path using an airborne microwave altimeter with the reference mean sea level, it can be seen that the retrieved sea surface height can track the fluctuations of the reference sea surface well. This indicates that after retracking, motion compensation, attitude correction, and reference surface correction, the airborne microwave altimeter results of this invention have good ranging capabilities. The attached figure corresponds to the calibration and accuracy verification process of the airborne microwave altimeter subsystem, demonstrating that this invention can provide stable and reliable basic data for subsequent sea surface height anomaly retrieval.

[0068] like Figure 6 As shown, the SLA results of sea surface height anomalies along the flight path obtained by the present invention are compared with the DUACS product of the Multi-Source Satellite Altimeter Data Unified Processing System. Over an overlapping flight segment of approximately 300 kilometers, the two methods maintain consistency in terms of trend, sign conversion, and amplitude distribution. The sea surface height anomaly gradually transitions from a negative anomaly on the cyclonic side to a positive anomaly on the anticyclonic side. Corresponding verification results show that the root mean square error compared to the DUACS product is approximately 0.44 cm, indicating that the present invention can provide sea surface height anomaly observation results with higher resolution along the flight path while maintaining consistency with the satellite dynamic background.

[0069] like Figure 7 As shown, the SLA results of sea surface height anomalies along the flight track obtained by this invention are compared with SWOT products from surface water and ocean topography satellites. Within the overlapping flight segments, both show good consistency in phase position and amplitude changes. Combined with cross-validation results, the root mean square error compared to the SWOT products is approximately 0.51 cm, indicating that the SLA of sea surface height anomalies along the flight track obtained by this invention can not only characterize mesoscale dynamic structures but also maintain good dynamic consistency at finer spatial scales, reflecting the advantages of UAV platforms in continuous observation at fine scales.

[0070] like Figure 8As shown, the airborne marine lidar inversion yielded the vertical profile of chlorophyll anomalies along the flight path. In this embodiment, the water body parameter is the chlorophyll concentration anomaly profile, and the figure shows the continuous variation characteristics of the subsurface structure with depth at different locations along the flight path. Combined with the verification results of synchronous in-situ observations, the airborne marine lidar can effectively characterize the vertical position and spatial variation characteristics of the subsurface chlorophyll peak, with an average absolute error of approximately 0.50 meters in the depth of the subsurface chlorophyll peak. This figure illustrates that the present invention can simultaneously obtain information on the vertical structure inside the water body while conducting sea surface dynamic observations, thus providing crucial support for quasi-three-dimensional ocean exploration.

[0071] like Figure 9 The diagram shown is a quasi-three-dimensional structural illustration, including sea level height anomalies, inverted upper-layer thermal structures, and synchronized chlorophyll anomaly vertical profiles within the same track-based coordinate system. This invention fuses the track-based sea level height anomaly (SLA), the chlorophyll anomaly vertical profile, and the upper-layer internal thermal structure further reconstructed based on the sea level height anomaly into a unified track-based coordinate system, forming a quasi-three-dimensional oceanographic detection result. Figure 9 The upper part of the figure shows the spatial correspondence between the UAV track and the background field of sea surface height anomalies; the middle part shows the vertical structural distribution of water parameters along the track; and the lower part shows the upper internal thermal structure reconstructed based on sea surface height anomalies. As can be seen from the figure, in the cyclonic vortex region, the sea surface height anomaly is negative, the corresponding internal thermal structure exhibits an upward characteristic, and the subsurface chlorophyll peak in the water parameter profile becomes shallower and stronger. In the anticyclonic vortex region, the sea surface height anomaly is positive, the corresponding internal thermal structure exhibits a downward characteristic, and the subsurface chlorophyll peak becomes relatively deeper and weaker. This invention can reveal the correspondence between sea surface dynamic signals, internal thermal structure of water bodies, and vertical structure of ecological parameters under the same spatiotemporal reference, and realize quasi-three-dimensional detection of the physical-ecological coupling process of the upper ocean. As can be seen from the figure, a sea surface depression of about 10 centimeters can correspond to an upward shift of the subsurface chlorophyll peak of about 12 meters and an enhancement of subsurface chlorophyll of about 0.15 micrograms / liter, which largely reveals the modulating effect of dipole vortex surface dynamics on internal ecology.

[0072] This invention provides a method and system for three-dimensional ocean detection based on unmanned aerial vehicles (UAVs) that integrates microwave and laser technologies. Using the results of synchronous microwave and laser detection as the data basis, the system performs calculations of sea surface height anomalies, inversion of internal thermal structures, and inversion of water body parameter profiles to achieve quasi-three-dimensional ocean detection that corresponds to sea surface dynamic signals, the internal thermal structure of the upper ocean, and vertical parameters of the water body.

[0073] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A method for three-dimensional ocean exploration based on unmanned aerial vehicles (UAVs) integrating microwave and laser technologies, characterized in that: Includes the following steps: Step 1: Target Sea Area Identification and Mission Planning By combining the type of ocean process to be observed, the endurance of the UAV, the flight airspace conditions, and the needs of on-site collaborative observation, the target sea area is identified and the mission is planned, and mission execution parameters and candidate observation schemes are formed. Step 2: Based on the sea surface height anomaly data from the satellite altimeter, determine the target area and the UAV flight path: Based on the sea surface height anomaly background field fused from multi-source satellite radar altimeters, the target sea area is identified, the target region is determined, and UAV flight survey lines are generated. Step 3: Simultaneously acquire synchronous detection data from multiple sensors; Using a drone equipped with a microwave altimeter and marine lidar, and with a unified time reference, unified navigation and attitude information, and a unified geographic reference system provided by a global navigation satellite system / inertial navigation system, synchronous detection data is acquired along the flight survey line. The synchronous detection data includes microwave echo sequences, laser echo waveforms, and corresponding positioning attitude data. Step 4: Joint inversion of ocean structure driven by synchronous detection data: Based on synchronous detection data, the sea surface dynamic field, internal thermal structure and water body parameter profiles were jointly inverted to obtain the sea surface height anomaly SLA along the track, the vertical thermal structure of the upper ocean and the vertical profile of chlorophyll anomaly, respectively. Step 5: Co-registration and fusion of microwave and laser synchronous detection results and construction of quasi-3D ocean structure: Constrained by the unified time reference and unified geographic reference system established in step three, the sea surface height anomaly SLA, upper ocean vertical thermal structure, and chlorophyll anomaly vertical profile obtained in step four are mapped to the unified track coordinate system to form a quasi-three-dimensional ocean detection product with the same track, time, and geographic reference, and the ocean quasi-three-dimensional detection results are output. Step four involves the joint inversion of the sea surface dynamic field, internal thermal structure, and water parameter profiles, as follows: Step 41, Solving for sea surface height anomalies using microwave altimetry: Pulse compression and waveform retracking were performed on the microwave echo sequence to obtain the one-way geometric slant range from the antenna phase center to the instantaneous sea surface. ; By combining the high-frequency trajectory and attitude information obtained from GNSS / INS calculations, motion compensation and lever correction are performed to obtain the sea surface height sequence (SSH) along the track. After removing the mean sea level and applying geophysical corrections, the sea surface height anomaly (SLA) along the track is obtained. The geophysical corrections include tidal corrections, solid earth tidal corrections, polar tidal corrections, anti-pressure corrections, and system residual bias corrections. Step 42, Internal thermal structure inversion: Using the sea surface height anomaly (SLA) along the navigation track as input, and combining spatiotemporal parameters such as latitude and time index, the sea surface height change signal is inverted based on a pre-trained mapping model to obtain the vertical thermal structure of the upper ocean. Step 43, Laser Profile Inversion: The laser echo waveform is preprocessed and converted from the time domain to the depth domain to obtain the backscattering profile of the water body. Based on the regional inversion framework or the parameter optimization inversion framework, a depth-resolved vertical profile of chlorophyll anomalies is obtained. In step 41, the slope distance The ranging model is represented as: (1) in, At the speed of light, The sampling start time, For system hardware latency, The leading edge feature point index determined by the re-tracking algorithm, The number of sampling points in the distance direction. This represents the time resolution after pulse compression. The expression for the sea surface altitude sequence SSH along the track is: (2) Where H is the height of the UAV relative to the reference ellipsoid. The antenna's angle from the nadir, determined by attitude information; The expression for the sea surface height anomaly (SLA) along the track is: (3) MSS stands for Mean Sea Level Model. Geophysical correction; In step 42, the pre-trained mapping model is a neural network model, and its output vector is represented as follows: (8) in, This represents the temperature value or temperature anomaly value of the i-th depth layer; During model training, the network parameters are optimized by minimizing the mean square error between the predicted profile and the reference profile. (9) in, For reference temperature profile, The model predicts the temperature profile, where N is the number of training samples. In step 43, the laser received signal satisfies the following lidar equation: (10) in, Let A be the echo signal at depth z, and A be the system calibration constant. The volume scattering function is 180°. The diffuse decay coefficient; The effective detection depth of the laser is the maximum effective depth corresponding to the water echo signal signal-to-noise ratio dropping to a preset threshold; a signal-to-noise ratio of 1 is used as the effective detection depth threshold.

2. The ocean three-dimensional detection method based on unmanned aerial vehicle (UAV) fusion of microwave and laser as described in claim 1, characterized in that, Perform parity-even sampling differential quality assessment on the sea surface altitude sequence along the track: The sequence of sea surface altitudes along a flight path in a certain frequency band is defined as follows: Divide it into odd sampled subsequences And even sampling subsequence Then the difference sequence is: (4) Perform linear fitting on the difference sequence: (5) The residual sequence is then: (6) If the standard deviation of the residual sequence is The effective altimetry accuracy of the original sea surface altitude sequence along the navigation track is: (7) The above evaluation results of the odd-even sampling differential accuracy are used to determine the quality of microwave altimetry data and to mark the output confidence level.

3. The ocean three-dimensional detection method based on unmanned aerial vehicle (UAV) fusion of microwave and laser as described in claim 1, characterized in that, In step three, the microwave altimeter is a Ka / Ku dual-frequency microwave altimeter, and the marine lidar is a blue-green dual-wavelength marine lidar with wavelengths of 486 nm and 532 nm, respectively.

4. The ocean three-dimensional detection method based on unmanned aerial vehicle (UAV) fusion of microwave and laser as described in claim 1, characterized in that, The results of the quasi-three-dimensional ocean exploration are expressed as follows: (11) Where s is the coordinate along the track, SLA(s) is the sea surface height anomaly along the track, T(s,z) is the internal thermal structure profile, P(s,z) is the vertical profile of chlorophyll anomaly, and Q(s,z) is the quasi-three-dimensional ocean exploration result.

5. A marine three-dimensional detection system based on unmanned aerial vehicles (UAVs) integrating microwave and laser technologies, characterized in that: Applied to the method as described in any one of claims 1-4, comprising: The mission planning module is used to identify target sea areas based on sea surface height anomaly data fused from multi-source satellite radar altimeters, generate UAV flight survey lines, and output flight altitude, flight speed, heading, survey line spacing, and collaborative on-site station parameters. The data acquisition module includes a microwave altimeter unit, a marine lidar unit, and a GNSS / INS navigation and attitude determination unit. It is used to simultaneously acquire microwave echo sequences, laser echo waveforms, and corresponding positioning and attitude data during the flight of the UAV along the flight survey line set by the mission planning module. The microwave altimeter processing module is used to process the microwave echo sequence acquired by the microwave altimeter radar altimeter unit in the data acquisition module to obtain the change signal of sea surface altitude anomaly (SLA) along the track. The internal thermal structure inversion module uses a pre-trained mapping model to invert the vertical thermal structure of the upper ocean based on the change signal of the sea surface height anomaly (SLA) along the track. The laser profile processing module is used to preprocess, perform depth domain conversion, and invert water parameters on the laser echo waveform acquired by the data acquisition module to generate a vertical profile of chlorophyll anomalies along the flight path. The fusion and reconstruction module is used to perform co-registration and fusion of surface height anomalies (SLA), upper ocean vertical thermal structure, and chlorophyll anomaly vertical profiles along the navigation track under a unified time reference and geographic reference system to generate quasi-three-dimensional ocean exploration results. The data storage and display module is used to store and display the quasi-three-dimensional marine exploration results generated by the fusion reconstruction module.

6. The ocean three-dimensional detection system based on unmanned aerial vehicle (UAV) fusion of microwave and laser as described in claim 5, characterized in that, The data acquisition module also includes an auxiliary sensor unit, which includes an infrared imaging unit and an optical polarization imaging unit, used to identify sea surface temperature texture, specular reflection areas, white waves, cloud and rain obscured areas, or strong glare areas. The microwave altimetry processing module is equipped with a quality control unit. The quality control unit is used to perform abnormal segment removal based on GNSS / INS attitude thresholds, system delay and transmit power stability monitoring based on internal loop calibration, abnormal echo screening based on microwave echo waveform morphology, and cross-validation based on satellite and / or field observations on the original microwave echo sequence and corresponding GNSS / INS attitude data. Combined with the evaluation results of odd-even sampling differential accuracy, the quality control unit outputs quality labels or confidence information for the microwave altimetry data.

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