Multi-source aviation remote sensing data acquisition apparatus, system and control method

Abstract

Disclosed in the present invention are a multi-source aviation remote sensing data acquisition apparatus, system and control method, which are applied to the technical field of aerial survey remote sensing. The apparatus comprises: a flight platform and an airborne device disposed on the flight platform. The airborne device comprises: a multi-sensor ultra-compact integrated device, an airborne integrated synchronization control device, and a GNSS receiving antenna. The multi-sensor ultra-compact integrated device and the airborne integrated synchronization control device are connected by means of cables, and the GNSS receiving antenna is disposed on an upper end face of the flight platform. The multi-sensor ultra-compact integrated device is used for acquiring multi-source remote sensing data; and the airborne integrated synchronization control device is used for controlling the operation of the multi-sensor ultra-compact integrated device. The present invention ultra-compactly integrates a LiDAR, a hyperspectral camera, a thermal infrared camera, and a visible-light camera on the basis of a high-precision inertial navigation system, and achieves efficient synchronous acquisition of texture, spectral, temperature, and geometric information by means of using an integrated control subsystem.

Description

A multi-source aerial remote sensing data acquisition device, system and control method Technical Field

[0001] The present invention relates to the field of aerial survey and remote sensing technology, and more particularly to a multi-source aerial remote sensing data acquisition device, system and control method. Background Art

[0002] Aerial remote sensing is an important means of obtaining surface information and is widely used in land and resources surveys, mapping, national defense, emergency response, and other fields. With the advancement of aerial remote sensing technology, the demand for aerial remote sensing data has gradually expanded from single optical images to multiple types of remote sensing data, including laser point clouds, quantitative spectra, and thermal radiation information. Limited by the dimensions of the flight platform's hatch, payload bay, optical window, and payload capacity, most current aerial remote sensing platforms can only carry no more than two remote sensing sensors simultaneously. Therefore, acquiring comprehensive information on a target's texture, spectrum, thermal radiation, geometry, and other elements requires multiple flights, each equipped with different types of sensors. However, this approach is inefficient and costly due to airspace and weather constraints. Furthermore, both the aerial platform and the atmospheric environment are less stable than satellites and space, making it difficult to ensure spatial consistency of remote sensing data acquired across multiple flights. This often prevents the fusion of these multiple remote sensing data types.

[0003] With the development of technologies such as aircraft, sensors, and image processing, the integration of multiple types of sensors on the same platform has become a development trend in aerial remote sensing. In recent years, domestic and foreign manufacturers have integrated multiple sets of multi-source remote sensing systems, but they all have problems such as poor multi-sensor integration, poor flight platform adaptability, low payload synchronization control accuracy, difficulty in data synchronization collection, and difficulty in data fusion. These problems have seriously affected the efficiency and quality of data acquisition and greatly increased the cost of use.

[0004] Therefore, it is an urgent problem for those skilled in the art to propose a multi-source aerial remote sensing data acquisition device, system and control method to solve the difficulties existing in the prior art.

[0005] Summary of the Invention

[0006] In view of this, the present invention provides a multi-source aerial remote sensing data acquisition device, system and control method, which uses a single attitude position measurement unit (POS system) to ultra-compactly integrate lidar, hyperspectral camera, thermal infrared camera and visible light camera. Based on the integrated control system, it realizes the comprehensive and synchronous acquisition of texture, spectrum, temperature and geometric information with temporal and spatial consistency, which can solve the problems of consistency of multi-sensor observation targets, stability of geometric relationships and ease of use.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A multi-source aerial remote sensing data acquisition device comprises: a flight platform and airborne equipment arranged on the flight platform;

[0009] The airborne equipment includes: multi-sensor ultra-compact integrated equipment, airborne integrated synchronous control equipment, and GNSS receiving antenna. The multi-sensor ultra-compact integrated equipment and the airborne integrated synchronous control equipment are connected by cables, and the GNSS receiving antenna is set on the end face of the flight platform;

[0010] Multi-sensor ultra-compact integrated device for collecting multi-source remote sensing data;

[0011] Airborne integrated synchronization control equipment, used to control the operation of multi-sensor ultra-compact integrated equipment;

[0012] GNSS receiving antennas, which convert radio signals transmitted by satellites into electrical current for use by receiver electronics;

[0013] The multi-sensor ultra-compact integrated device includes: lidar, hyperspectral camera, visible light camera, thermal infrared camera, inertial measurement unit (IMU) and reference mounting plate;

[0014] The reference mounting plate is provided with mounting reference edges for each sensor, which is used to provide a mounting reference structure for multiple types of sensors; the reference axis systems of each sensor and the inertial measurement unit (IMU) are orthogonally aligned;

[0015] The laser radar, visible light camera and thermal infrared camera are all installed at the lower end of the reference mounting plate; the laser radar is used to obtain laser point cloud data of ground objects; the visible light camera is used to obtain optical images of ground objects; and the thermal infrared camera is used to obtain thermal infrared images of ground objects.

[0016] The hyperspectral camera and inertial measurement unit (IMU) are installed on the upper end of the reference mounting plate. The hyperspectral camera is used to obtain quantitative spectral data of ground objects. The inertial measurement unit (IMU) is used to provide position and attitude information for the lidar, hyperspectral camera, visible light camera, and thermal infrared camera, thereby obtaining aerial remote sensing data with geographic information.

[0017] The multi-sensor ultra-compact integrated device is composed of multiple types of remote sensing sensors in an upper and lower layered structure, which are rigidly connected by a reference mounting plate.

[0018] Optionally, the base mounting plate is further provided with a tail support, a bottom mounting frame, a top mounting frame, and a plurality of shock absorbers; wherein,

[0019] The tail support is set on the lower end surface of the reference mounting plate and fixed to one side of the laser radar by bolts;

[0020] The bottom mounting frame is set on the lower end surface of the reference mounting plate and is fixed to the corresponding side of the laser radar and the tail support by bolts. The visible light camera and thermal infrared camera are both fixedly connected to the bottom mounting frame by bolts;

[0021] The top mounting bracket is set on the end surface of the reference mounting plate and is fixedly connected to the hyperspectral camera by bolts;

[0022] There are multiple shock absorbers, all of which are set at the lower end of the reference mounting plate and located at the four corners of the reference mounting plate. The shock absorbers are fixedly connected to the reference mounting plate by bolts to reduce the impact of platform vibration on each sensor during flight.

[0023] Optionally, the onboard integrated synchronous control equipment includes: industrial control host, integrated power supply and distribution module, combined navigation host, telescopic console, display, aviation shock-absorbing cabinet, data storage unit; among which,

[0024] Aviation shock-absorbing cabinet, used to integrate industrial control host, integrated power supply and distribution module, combined navigation host, telescopic console, display and data storage unit;

[0025] The industrial control host, integrated power supply and distribution module, and data storage unit are all installed inside the aviation shock-absorbing cabinet and fixedly connected to the aviation shock-absorbing cabinet via bolts. The industrial control host is used to issue instructions to each functional module, control the power supply, acquisition, and storage working status of each sensor, and set the operating parameters of each sensor. The integrated power supply and distribution module is used to convert the power supply voltage of the flight platform to meet the power requirements of each sensor. The data storage unit is used to store the laser point cloud, hyperspectral image, thermal infrared image, and visible light image data generated during the data acquisition process.

[0026] One end of the telescopic console is embedded in the aviation shock-absorbing cabinet away from the data storage unit, and the other side of the telescopic console can be extended out of the aviation shock-absorbing cabinet. The telescopic console is used for manually operating the industrial control host equipment;

[0027] The integrated navigation host is set on the aviation shock-absorbing cabinet and on the same side as the telescopic console. It is fixed to the aviation shock-absorbing cabinet by bolts. The integrated navigation host is used to receive and integrate the measurement data of the global navigation satellite system and the inertial measurement unit (IMU) to obtain three-dimensional position, velocity and attitude information;

[0028] The display is set on the aviation shock-absorbing cabinet and on the same side as the telescopic console, and is located above the telescopic console. The display is fixed to the aviation shock-absorbing cabinet by bolts. It is used to display the working parameters of each device and display the working status and data acquisition quality of each sensor in real time during operation.

[0029] A multi-source aerial remote sensing data acquisition system comprises any of the multi-source aerial remote sensing data acquisition devices described above, and further comprises: a power supply and distribution subsystem, an integrated control subsystem, a large-capacity data high-speed storage subsystem, and a real-time display and monitoring subsystem; wherein,

[0030] Power supply and distribution electronic system, used to distribute power supply that meets voltage and power requirements to various sensors and other electrical equipment;

[0031] The integrated control subsystem is used to issue control instructions, centrally control multiple sensors for data collection, storage, and display operations, and ensure the synchronization of the time of each sensor;

[0032] Large-capacity, high-speed data storage subsystem to meet the storage requirements of large data volumes and high data rates of multiple sensors;

[0033] The real-time display and monitoring subsystem is used to display the data obtained by each sensor in real time during the operation process and monitor the working status parameters of the sensor.

[0034] Optionally, the power supply and distribution subsystem includes an isolated DC / DC module and a rack-mounted inverter; wherein,

[0035] The isolated DC / DC module is used to convert the voltage of the DC power provided by the flight platform;

[0036] The rack-mounted inverter is used to convert DC power into AC power. The DC voltage input by the isolated DC / DC module is converted into AC voltage;

[0037] The integrated control subsystem includes a time synchronization module and a multi-sensor synchronization control module;

[0038] The time synchronization module includes a high-precision time unit and a sensor timing unit, which are used to establish a high-precision time reference;

[0039] The multi-sensor synchronization control module is used to comprehensively control multiple sensors for data acquisition, storage and display operations.

[0040] Optional, high-capacity data high-speed storage subsystem consisting of Oculink connectors and disk arrays for real-time storage of data collected by multiple sensors onboard;

[0041] Among them, the Oculink connector is used to connect the disk array to the integrated control subsystem and perform PCIE4.0 connection between the disk array and the integrated control subsystem;

[0042] The disk array is composed of a first solid-state hard drive, a second solid-state hard drive, and a third solid-state hard drive. The first solid-state hard drive is used to store laser point cloud data and thermal infrared image data, the second solid-state hard drive is used to store visible light image data, and the third solid-state hard drive is used to store hyperspectral image data and attitude position measurement data.

[0043] The real-time display and monitoring subsystem includes a data analysis module and a data quick view module;

[0044] The data parsing module is used to parse multiple types of data and perform quick image preprocessing;

[0045] The data quick view module is used to scroll, refresh, and change the view of the generated graph in different quick view modes.

[0046] A multi-source aerial remote sensing data acquisition control method, using any of the multi-source aerial remote sensing data acquisition systems described above, comprises the following steps:

[0047] S1. Connect the power line, trigger line, and data line of each sensor and power on the device;

[0048] S2. Perform multi-sensor integrated control through the host computer control software in the integrated control subsystem, configure the parameters of each sensor, set the width and period of the trigger pulse, and transmit the setting instructions to the main control circuit board;

[0049] S3. Start the operation and data collection of each sensor with one click manually, obtain the calibration parameters after the sensor calibration flight, and then synchronously collect and store the aerial remote sensing data;

[0050] S4. During the acquisition process, the key parameters and operating status of each sensor are displayed in real time, and the data collected by each sensor is quickly displayed. After the task is completed, the operation of the sensor and data acquisition can be terminated with one click.

[0051] Optionally, the sensor calibration in S3 is as follows:

[0052] S31. Select and lay out a calibration site, where there are buildings for laser radar calibration and the ground features have reflectivity;

[0053] S32. Set up the inspection and calibration route, adopt the vertical cross and large lateral overlap laying method, and evenly distribute multiple control points along the route direction;

[0054] S33. Fly according to the set calibration route and collect lidar point cloud data;

[0055] S34, automatically extract the connecting surface between the overlapping flight strips and obtain the centroid coordinates (X 84 , Y 84 , Z84 );

[0056] S35, using the center-of-gravity coordinates as the connection points of different flight paths, and then establishing an error equation based on the difference between the center-of-gravity coordinates of the connection surface and the observation equation of the laser foot point;

[0057] S36. Suppose there are N connection points, establish N error equations, and apply the least squares principle to solve the installation angle error.

[0058] Optionally, the synchronous collection and storage of aerial remote sensing data in S3 is as follows:

[0059] S331: Establishing a time reference based on the GNSS information provided by the integrated navigation host and the differential crystal oscillator;

[0060] S332: Calibrate the IMU measurement time using the 1PPS signal sent by the integrated navigation host;

[0061] S333: Use an improved Kalman filter algorithm to reduce GNSS observation data delay and IMU data update calculation delay;

[0062] S334: Use the sensor timing unit to synchronize the time of the lidar, hyperspectral camera, visible light camera, and thermal infrared camera, and complete the synchronous collection of multi-source aerial remote sensing data.

[0063] Optionally, the specific content of S333 is:

[0064] The first step is to save the output values ​​of the IMU accelerometer and gyroscope when the integrated navigation host starts sampling the GNSS signal. When the GNSS observation data is actually received, it starts to calculate and update the current attitude, velocity and position of the flight platform in real time.

[0065] First, the attitude differential equation is used to solve the attitude: and And use the formula to perform t k-1 Time to t k The attitude matrix update at this moment:

[0066] Among them, b represents the flight platform coordinate system, i represents the inertial coordinate system, n represents the navigation coordinate system, and the matrix is the attitude relationship of the b system relative to the i system expressed by quaternions, represent Differentiation with respect to time, represent Differentiation with respect to time, Represents the projection of the angular velocity of system i relative to system n in system n, Represents the projection of the angular velocity of system n relative to system i in system n, Represents the attitude transformation matrix from the inertial coordinate system to the navigation coordinate system, Represents the direct output of the IMU, which is the projection of the angular velocity of the b system relative to the i system in the b system. It means that when the i system is used as the reference, the b system starts from t k-1 Time to t k The rotation change at the moment is given by Sure, Represents in t k The attitude transformation matrix from the flight platform coordinate system to the inertial coordinate system at any moment, Represents in t k-1 The attitude transformation matrix from the flight platform coordinate system to the inertial coordinate system at any moment, Represents t k The attitude conversion matrix from the inertial coordinate system to the navigation coordinate system at the moment, Represents n series from t k-1 Time to t k The rotation changes of the moment, Represents t k-1 The attitude transformation matrix from the inertial coordinate system to the navigation coordinate system at any moment;

[0067] Then, the velocity differential equation is used to update the velocity state and the integral is obtained:

[0068] in, t k-1 The speed of time, is the n-system specific force velocity increment, is the velocity increment of harmful acceleration, t k the speed of the moment;

[0069] Finally, the position update calculation is performed using the position differential equation:

[0070] Among them, P k t k The position state matrix at the moment, is the IMU at t k The speed value output at each moment, is the transformation matrix, P k-1 t k-1 The position state matrix at the moment, t k-1 The speed value output at the moment, ΔT is the time increment;

[0071] The second step is to first calculate the GNSS sampling time, i.e., t k The state parameter estimator and state parameter covariance estimator at the moment are then transferred to the current moment, that is, the update calculation is completed, t j At time j>k, the state transition is performed using the following formula to correct the delay error at the current moment:

[0072] in, According to t k to t j k observation vector value pairs at time t j The state parameter vector X at the moment j The linear minimum variance estimate made, Φ j / k is the state transition matrix, t k The state parameter vector X at the moment k The updated estimate of is the covariance matrix of the forecast error, is the covariance matrix of the state parameters, is the transpose of the state transfer matrix, M j,k+1 is the correction matrix factor.

[0073] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides a multi-source aerial remote sensing data acquisition device, system and control method, which have the following beneficial effects:

[0074] Through structural design and system development, a high-precision inertial navigation system is ultra-compactly integrated with lidar, hyperspectral camera, thermal infrared camera and visible light camera. The integrated control subsystem is used to achieve efficient and synchronous acquisition of texture, spectrum, temperature and geometric information. The proposed control method ensures that the multi-source data has good temporal and spatial consistency, significantly improves the absolute positioning accuracy of the data and the mutual registration accuracy of the multi-source data, meets the needs of joint processing and fusion applications of multi-source remote sensing data, and greatly increases the amount of effective information obtained in a single flight. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0076] FIG1 is a schematic diagram of the three-dimensional structure of an ultra-compact integrated multi-sensor device provided by the present invention;

[0077] FIG2 is a schematic diagram of the split structure of the multi-sensor ultra-compact integrated device provided by the present invention;

[0078] FIG3 is a side view of the installation of the multi-sensor ultra-compact integrated device provided by the present invention;

[0079] FIG4 is a schematic diagram of the composition structure of the airborne integrated synchronization control device provided by the present invention;

[0080] FIG5 is a schematic diagram of the composition of a multi-source aerial remote sensing data acquisition system provided by the present invention;

[0081] FIG6 is a schematic diagram of the composition of the power supply and distribution electronic system provided by the present invention;

[0082] FIG7 is a schematic diagram of the composition of the integrated control subsystem provided by the present invention;

[0083] FIG8 is a schematic diagram showing the composition of a large-capacity data high-speed storage subsystem and a real-time display and monitoring subsystem provided by the present invention;

[0084] FIG9 is a flow chart of a multi-source aerial remote sensing data acquisition control method provided by the present invention;

[0085] Among them: 1-LiDAR, 2-Hyperspectral camera, 3-Visible light camera, 4-Thermal infrared camera, 5-Inertial measurement unit IMU, 6-Benchmark mounting plate, 7-Tail support, 8-Bottom mounting frame, 9-Top mounting frame, 10-Shock absorber, 11-Mounting handle, 12-Threaded hole, 13-Heightening pad, 14-Cabin floor, 15-Mounting adapter plate, 16-Aerial survey window, 17-Industrial control host, 18-Integrated power supply and distribution module, 19-Combined navigation host, 20-Telescopic console, 21-Display, 22-Aviation shock-absorbing cabinet, 23-Data storage unit. DETAILED DESCRIPTION

[0086] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0087] The present invention discloses a multi-source aerial remote sensing data acquisition device, comprising: a flight platform, which is a common model of fixed-wing manned aircraft, with an aerial survey window 16 having a radius of not less than 450 mm on the belly of the cabin, and aircraft models include but are not limited to Yun-5, Yun-12, Big Brown Bear, Cessna 208, and King Air 350;

[0088] The airborne equipment installed on the flight platform includes a multi-sensor ultra-compact integrated integrated device, an airborne integrated synchronous control device and a GNSS receiving antenna. The multi-sensor ultra-compact integrated integrated device and the airborne integrated synchronous control device are connected by cables, and the GNSS receiving antenna is set on the end face of the flight platform. Among them, the multi-sensor ultra-compact integrated integrated device is used to collect multi-source remote sensing data; the airborne integrated synchronous control device is used to control the operation of the multi-sensor ultra-compact integrated device; the GNSS receiving antenna is used to convert the radio signals transmitted by the satellite into electric current used by the receiver electronic devices.

[0089] The multi-sensor ultra-compact integrated device, as shown in Figures 1 and 2, consists of a reference mounting plate 6, a lidar 1, a hyperspectral camera 2, a visible light camera 3, a thermal infrared camera 4, an inertial measurement unit (IMU) 5, multiple shock absorbers 10, a tail support 7, a bottom mounting frame 8, and a top mounting frame 9, and is used to acquire multi-source remote sensing data.

[0090] Furthermore, the multi-sensor ultra-compact integrated device, because the sizes of multiple types of sensors are relatively large, parallel distribution will result in the horizontal size of the entire device being too large, making it impossible to adapt to multiple flight platforms at the same time. Therefore, a top-down layered structure is adopted, and multiple types of sensors are combined by rigid connection through the reference mounting plate 6;

[0091] Since the field of view of the hyperspectral camera 2 is small and is a linear field of view, the field of view of the laser radar 1, visible light camera 3, and thermal infrared camera 4 is large. Therefore, the laser radar 1, visible light camera 3, and thermal infrared camera 4 are arranged in the lower structure closer to the optical window, and the hyperspectral camera 2 and the inertial measurement unit IMU5 with no field of view requirement are arranged in the upper layer; this arrangement scheme can minimize the entire system's requirement for the size of the flight platform's observation window and increase the system's platform adaptability.

[0092] The reference mounting plate 6 is made of lightweight steel with high rigidity and has an outer contour of 560mm×550mm (length×width). It is provided with mounting reference edges for various sensors and is used to provide a stable and reliable mounting reference structure for multiple types of sensors, ensuring that the observation fields of each sensor match and correspond, and the reference axis systems of each sensor and the inertial measurement unit IMU5 are orthogonally aligned, and the placement relationship between them is stable and unchanged, providing a good hardware foundation for ensuring the spatial consistency of multi-source remote sensing data.

[0093] The laser radar 1 is an airborne long-range laser scanner with a 60° field of view, a laser emission frequency of 2000KHz, and a parallel line scanning method. It can simultaneously emit 45 pulses in the air and has the ability to record more than 14 echoes. The maximum flight operating altitude relative to the ground is 3900m@20% reflectivity and 5800m@60% reflectivity. It has full waveform digital multi-echo processing capabilities and is used to obtain laser point cloud data of ground targets. It is set on the lower end face of the reference mounting plate 6. The tail support 7 is fixed to one side of the laser radar 1 by bolts using the threaded holes 12 on both sides and the tail. The bottom mounting frame 8 is fixed to the side of the laser radar 1 corresponding to the tail support 7 by bolts. The bottom mounting frame 8 and the tail support 7 are fixedly connected to the reference mounting plate 6 by bolts.

[0094] Hyperspectral camera 2 is an airborne full-spectrum hyperspectral system with a spectral detection range of 380nm-2500nm, a field of view of 32.3°, 384 scanning line pixels, and a spectral resolution of 3.5nm / 10nm. It is used to obtain quantitative spectral data of ground objects. It is installed on the upper end surface of the reference mounting plate 6 and is mounted on the top mounting frame 9 using its side threaded holes 12. The top mounting frame 9 and the reference mounting plate 6 are fixedly connected by bolts. Both the top mounting frame 9 and the reference mounting plate 6 are provided with observation slits to ensure the passability of the field of view of the hyperspectral camera 2.

[0095] Visible light camera 3 is a medium-format optical aerial survey camera with a 30° field of view, an effective pixel count of 11664×8750, and a format size of 33mm×44mm. It is mounted on the lower end surface of reference mounting plate 6 and fixedly connected to bottom mounting frame 8 by bolts. It is used to obtain high-definition optical images of ground objects.

[0096] Thermal infrared camera 4 is a wide-band, uncooled infrared thermal imager with a field of view of 45°×37°, an effective pixel count of 640×512, an operating spectrum wavelength range of 7μm to 14μm, an equivalent measurement accuracy of NEdT ≤ 45mK (at 30°C), an absolute temperature accuracy of 1K or 1%, and a temperature measurement range of -20°C to 150°C. It is mounted on the lower end surface of reference mounting plate 6, side by side with visible light camera 3, and fixedly connected to bottom mounting frame 8 by bolts to obtain thermal infrared images of ground objects.

[0097] The inertial measurement unit (IMU) 5 is an ultra-high-performance, metrological-grade fiber-optic integrated navigation system with a positioning accuracy of ≤1cm, a velocity error of ≤0.005m / s, and a roll / pitch angle of ≤0.003°. The IMU5 data recording frequency is >200Hz, and the post-processing heading accuracy reaches 0.004°. It is directly mounted on the upper end face of the reference mounting plate 6 through the bottom threaded hole 12 and fixed to the reference mounting plate 6 with bolts. It is used to provide accurate position and attitude information for the lidar 1, hyperspectral camera 2, visible light camera 3, and thermal infrared camera 4, assisting in the acquisition of high-precision aerial remote sensing data with geographic information.

[0098] The shock absorbers 10 are four T44 damping isolators with comprehensive shock absorption effects. They can effectively isolate vibrations and disturbances in all directions and frequencies and can withstand a load weight of more than 70 kg. They are installed on the lower end surface of the reference mounting plate 6, respectively located at the four corners of the rectangular base plate, and fixedly connected to the reference mounting plate 6 by bolts to reduce the impact of platform vibration on each sensor during flight.

[0099] The multi-sensor ultra-compact integrated device is installed using a sunken installation method and is placed in the aerial survey window 16. As shown in Figure 3, the outer contour dimensions of the lower sensor are 450mm×341mm (length×width). The device sinks the lower sensor below the cabin floor 14 by adding a customized raising pad 13 to the shock absorber 10 at the bottom of the reference mounting plate 6. The raising pad 13 is connected to the shock absorber 10 by bolts. The raising pad 13 is supported on the installation adapter plate 15 and fixed by bolts. The installation adapter plate 15 is attached to the cabin floor 14 and fixed to the cabin floor 14 by aircraft-specific bolts.

[0100] Furthermore, the height-raising pad 13 is made of 6061 aluminum alloy, with four M5 shock absorber mounting threaded holes reserved on the top, four M6 adapter plate mounting threaded holes reserved on the bottom, and a weight-reducing groove set in the middle, which can withstand a load weight of more than 100kg.

[0101] The onboard integrated synchronous control device, as shown in Figure 4, consists of an aviation shock-absorbing cabinet 22, an industrial control host 17, an integrated power supply and distribution module 18, a combined navigation host 19, a telescopic console 20, a display 21, and a data storage unit 23. It is connected to the multi-sensor ultra-compact integrated device via cables and fixed to the cabin floor 14 with anchor bolts.

[0102] The aviation shock-absorbing cabinet 22 is made of 2mm aluminum plate and is sandblasted black oxidized. It is used to integrate the industrial control host 17, the integrated power supply and distribution module 18, the integrated navigation host 19, the telescopic console 20, the display 21 and the data storage unit 23;

[0103] The industrial control host 17 is installed inside the aviation shock-absorbing cabinet 22 and is fixedly connected to the aviation shock-absorbing cabinet 22 by bolts. It is used to issue instructions to each functional module, control the power supply, collection, and storage working status of each sensor, and set the working parameters of each sensor;

[0104] The integrated power supply and distribution module 18 is installed inside the aviation shock-absorbing cabinet 22 and is fixedly connected to the aviation shock-absorbing cabinet 22 by bolts. It is used to convert the power supply voltage of the flight platform to meet the power requirements of various sensors;

[0105] The integrated navigation host 19 is set on the aviation shock-absorbing cabinet 22 and on the same side as the telescopic console 20, and is fixedly connected to the aviation shock-absorbing cabinet 22 by bolts. The integrated navigation host 19 is used to receive and integrate the measurement data of the global navigation satellite system and the inertial measurement unit IMU5 to obtain three-dimensional position, velocity and attitude information;

[0106] One end of the telescopic console 20 is embedded in the aviation shock-absorbing cabinet 22 away from the data storage unit 23, and the other side of the telescopic console 20 can be extended out of the aviation shock-absorbing cabinet 22. The telescopic console 20 is used to manually operate the industrial control host 17 equipment;

[0107] The display 21 is a foldable dual-screen device, which is installed on the aviation shock-absorbing cabinet 22 and on the same side as the telescopic console 20, and is located above the telescopic console 20. The display 21 is fixedly connected to the aviation shock-absorbing cabinet 22 by bolts, and is used to display the working parameters of each device and display the working status and data acquisition quality of each sensor in real time during operation.

[0108] The data storage unit 23 is installed inside the aviation shock-absorbing cabinet 22 and consists of a removable SSD solid-state hard drive array. The removable box is plug-and-play and adopts an adjustable lock design to allow the M.2 hard drive holder to slide freely. At the same time, a key chain is used to fix the drawer to the aviation shock-absorbing cabinet 22. It is used to store laser point clouds, hyperspectral images, thermal infrared images and visible optical image data generated during the data acquisition process.

[0109] A multi-source aerial remote sensing data acquisition system, as shown in Figure 5, consists of a power supply and distribution subsystem, an integrated control subsystem, a large-capacity data high-speed storage subsystem, and a real-time display and monitoring subsystem;

[0110] The power supply and distribution electronic system is used to distribute power supply that meets the voltage and power requirements to various sensors and other electrical equipment; as shown in Figure 6, it mainly includes an isolated DC / DC module and a rack-mounted inverter. The isolated DC / DC module is used to convert the voltage of the DC power provided by the flight platform to provide DC power that meets the corresponding voltage requirements for the lidar 1, hyperspectral camera 2, visible light camera 3, thermal infrared camera 4, inertial measurement unit IMU5, and integrated navigation host 19. The rack-mounted inverter is used to convert DC power into AC power. The DC voltage input by the isolated DC / DC module is converted into AC voltage, which in turn supplies power to the industrial control host 17, display 21, and spare sockets.

[0111] The integrated control subsystem is used to issue instructions and centrally control multiple sensors to perform data acquisition, storage, and display operations, and ensure the precise synchronization of the time of each sensor. As shown in Figure 7, it includes a time synchronization module and a multi-sensor synchronization control module. The time synchronization module includes a high-precision time unit and a sensor timing unit, which are used to provide a high-precision standard time and ensure that the clock of each sensor can be synchronized with it with high precision. The laser radar 1 calculates the trigger acquisition time by receiving the PPS pulse signal and GPRMC time synchronization message of the attitude position measurement unit, and synchronizes the time to the system time of the device through the sensor timing unit. When the hyperspectral camera 2, visible light camera 3, and thermal infrared camera 4 receive control instructions to trigger photos, the system records the marker information (including time and position) of the attitude and position measurement unit at that moment, and uses this marker information to achieve spatiotemporal consistency matching with other types of sensors; the multi-sensor synchronization control module is used to comprehensively control multiple sensors for data acquisition, storage, and display operations. It triggers control instructions to the hyperspectral camera 2, visible light camera 3, thermal infrared camera 4, and attitude and position measurement unit through electrical signals, and triggers control instructions to the lidar 1 through PPS signals. The time synchronization module is used to achieve comprehensive synchronous control of each sensor;

[0112] A large-capacity, high-speed data storage subsystem is used to meet the storage requirements of large amounts of data and high data rates of multiple sensors. As shown in Figure 8, it is mainly composed of an Oculink connector and a disk array, and is mainly used to store massive amounts of data collected by multiple sensors on the machine in real time. The Oculink connector is used to connect the disk array to the integrated control subsystem, and to perform a PCIE4.0 connection between the disk array and the integrated control subsystem to meet the high-speed data access requirements. The disk array consists of a first solid-state drive, a second solid-state drive, and a third solid-state drive, with a designed storage capacity of 6TB. The first solid-state drive is used to store laser point cloud data and thermal infrared image data, the second solid-state drive is used to store visible light image data, and the third solid-state drive is used to store hyperspectral image data and attitude position measurement data, meeting the operation requirements of the entire system for more than 10 hours.

[0113] The real-time display and monitoring subsystem is used to display the data obtained by each sensor in real time during the operation and monitor the working status parameters of the sensors. As shown in Figure 8, it includes a data analysis module and a data quick view module. The data analysis module is used to analyze multiple types of data and pre-process quick views of images. The data quick view module is used to display the generated images in different quick view modes such as scrolling, refreshing, and changing the scene.

[0114] The present invention provides a multi-source aerial remote sensing data acquisition control method, as shown in FIG9 , comprising the following steps:

[0115] S1. Connect the power line, trigger line, and data line of each sensor and power on the device;

[0116] S2. Perform multi-sensor integrated control through the host computer control software in the integrated control subsystem, configure the parameters of each sensor, set the width and period of the trigger pulse, and transmit the setting instructions to the main control circuit board;

[0117] S3. Start the operation and data collection of each sensor with one click manually, obtain the calibration parameters after the sensor calibration flight, and then synchronously collect and store the aerial remote sensing data;

[0118] S4. During the acquisition process, the key parameters and operating status of each sensor are displayed in real time, and the data collected by each sensor is quickly displayed. After the task is completed, the operation of the sensor and data acquisition can be terminated with one click.

[0119] Furthermore, a multi-source aerial remote sensing data acquisition and control method is mainly implemented through two aspects. First, the designed installation reference structure ensures stability and reliability, ensures that the observation field of view of each sensor matches and corresponds, and that each sensor is orthogonally aligned with the reference axis system of the high-precision inertial measurement unit, and the placement relationship between them is stable and unchanged; second, the designed integrated control subsystem is used to centrally and uniformly control each sensor to achieve high-precision clock synchronization of each sensor.

[0120] The sensor calibration method mainly calibrates the sighting axis of the laser radar 1 to reduce the placement error between the sensor and the inertial measurement unit IMU5.

[0121] Specifically, the sensor calibration in S3 is as follows:

[0122] S31. Select and lay out a calibration site, where there are buildings for calibrating the laser radar 1 and the ground features have reflectivity;

[0123] S32. Set up the inspection and calibration route, adopt the vertical cross and large lateral overlap laying method, and evenly distribute multiple control points along the route direction;

[0124] S33. Fly according to the set calibration route and collect lidar point cloud data;

[0125] S34, automatically extract the connecting surface between the overlapping flight strips and obtain the centroid coordinates (X 84 , Y 84 , Z 84 );

[0126] S35, using the center-of-gravity coordinates as the connection points of different flight paths, and then establishing an error equation based on the difference between the center-of-gravity coordinates of the connection surface and the observation equation of the laser foot point;

[0127] S36. Suppose there are N connection points, establish N error equations, and apply the least squares principle to solve the installation angle error.

[0128] Specifically, S36 includes the angles between the laser radar 1 and the inertial measurement unit IMU5 in the three directions of roll, pitch and heading.

[0129] Furthermore, the synchronous collection and storage of aerial remote sensing data in S3 is as follows:

[0130] S331: Establishing a time reference based on the GNSS information provided by the integrated navigation host 19 and the differential crystal oscillator;

[0131] Specifically, the first step is to initialize the high-precision time unit in the time synchronization module and create two counters: the second-level time counter and the differential crystal pulse counter, which are used to record the PPS second pulse signal and the pulse signal of the differential crystal input respectively;

[0132] In the second step, the high-precision time unit receives the GPRMC message data output by the integrated navigation host 19, which is in the form of: GPRMC<field 1>, <field 2>, <field 3>..., which contains time information and positioning information;

[0133] The third step is to parse the precise time information in the GPRMC message data through the high-precision time unit and convert the information into the total number of seconds, and then use this value to initialize the second-level timer;

[0134] The fourth step is to use the differential crystal pulse counter to count the pulses input by the differential crystal oscillator and monitor the transition edge of the PPS second pulse signal input by the integrated navigation host 19. When the PPS second pulse signal generates a rising edge, the differential crystal pulse counter is cleared and restarted from 0, and the count value of the second time counter is increased by 1.

[0135] The fifth step is to integrate and accumulate the two counters to obtain a high-precision time base for unifying all sensors. Among them, the second-level time counter records the total number of seconds at the current moment, and the differential crystal pulse counter records the time from the current second to the next second.

[0136] S332: Calibrate the measurement time of the inertial measurement unit IMU5 using the 1PPS signal sent by the integrated navigation host 19;

[0137] Specifically, in the first step, the embedded microcontroller unit in the multi-sensor synchronization control module simultaneously receives the 1PPS signal sent by the integrated navigation host 19 and the sampling pulse signal sent by the IMU. After the 1PPS second pulse signal is triggered, the second-level time counter is used to obtain the GNSS full second time of the first 1PPS second pulse signal triggering;

[0138] The second step is to create an IMU sampling counter. The IMU sampling counter performs sampling at a higher frequency and records the number of sampling times in the IMU sampling counter. The embedded microcontroller unit is used to decode the data collected each time and compare it with the count of the second-level time counter at the previous moment to determine whether the second-level time has changed.

[0139] The third step is to use the judgment result to determine the time of the IMU data. If the second-level time has not changed, the current and previous IMU sampling counter results are subtracted, and then divided by the local crystal oscillator frequency to obtain the time interval between the two moments. The time interval is superimposed on the time of the IMU data at the previous moment to obtain the time of the current IMU data. If the second-level time has changed, first determine whether it is a 1PPS abnormality by the size of the change. If the change amplitude is not within the normal range of the local crystal oscillator frequency, it is determined to be abnormal, and the IMU data time is calculated using the method of no change in the second-level time. If it is determined to be a normal trigger of the next 1PPS, the current and IMU sampling counter results are subtracted from the second-level time result, and divided by the local crystal oscillator frequency to obtain the time difference between the current and full second moments. By adding this difference to the second-level time, the time of the current IMU data is obtained.

[0140] S333: Uses an improved Kalman filter algorithm to reduce GNSS observation data latency and IMU5 data update calculation latency;

[0141] Specifically, the first step is to save the output values ​​of the IMU accelerometer and gyroscope when the integrated navigation host 19 starts sampling the GNSS signal, and start calculating and updating the current attitude, velocity and position of the flight platform in real time when the GNSS observation data is actually received;

[0142] First, the attitude differential equation is used to solve the attitude: and And use the following formula to calculate t k-1 Time to t k The attitude matrix update at this moment: Among them, b represents the flight platform coordinate system, i represents the inertial coordinate system, n represents the navigation coordinate system, and the matrix is the attitude relationship of the b system relative to the i system expressed by quaternions, represent Differentiation with respect to time, represent Differentiation with respect to time, Represents the projection of the angular velocity of system i relative to system n in system n, Represents the projection of the angular velocity of system n relative to system i in system n, Represents the attitude transformation matrix from the inertial coordinate system to the navigation coordinate system, Represents the direct output of the IMU, which is the projection of the angular velocity of the b system relative to the i system in the b system. It means that when the i system is used as the reference, the b system starts from t k-1 Time to t k The rotation change at the moment is given by Sure, Represents in t k The attitude transformation matrix from the flight platform coordinate system to the inertial coordinate system at any moment, Represents in t k-1 The attitude transformation matrix from the flight platform coordinate system to the inertial coordinate system at any moment, Represents t k The attitude conversion matrix from the inertial coordinate system to the navigation coordinate system at the moment, Represents n series from t k-1 Time to t k The rotation changes of the moment, Represents t k-1 The attitude transformation matrix from the inertial coordinate system to the navigation coordinate system at any moment;

[0143] Then, the velocity differential equation is used to update the velocity state and the integral is obtained: in, t k-1 The speed of time, is the n-system specific force velocity increment, is the velocity increment of harmful acceleration, t k the speed of the moment;

[0144] Finally, the position update calculation is performed using the position differential equation: Among them, P k t k The position state matrix at the moment, is the IMU at t k The speed value output at each moment, is the transformation matrix, P k-1 t k-1 The position state matrix at the moment, t k-1 The speed value output at the moment, ΔT is the time increment.

[0145] The second step is to first calculate the GNSS sampling time (t k The state parameter estimator and state parameter covariance estimator of the time) are then transferred to the current time (update calculation is completed, t j At time, j>k), through the simultaneous formula Perform state transfer and correct the delay error at the current moment; According to t k to t j k observation vector value pairs at time t j The state parameter vector X at the moment j The linear minimum variance estimate made, Φ j / k is the state transition matrix, t k The state parameter vector X at the moment k The updated estimate of is the covariance matrix of the forecast error, is the covariance matrix of the state parameters, is the transpose of the state transfer matrix, M j,k+1 is the correction matrix factor.

[0146] S334: Use the sensor timing unit to perform timing on the lidar 1, hyperspectral camera 2, visible light camera 3, and thermal infrared camera 4, respectively, and complete the synchronous collection of multi-source aerial remote sensing data.

[0147] Specifically, first, the sensor timing unit in the time synchronization module is used to monitor the rising edge of the PPS pulse signal emitted by the combined navigation host 19, and the GPRMC message information emitted by the combined navigation host 19 is cached in the data queue; when the rising edge of the PPS pulse signal is monitored, the sensor timing unit takes out the most recent complete GPRMC message information from the data queue within a fixed time interval, and passes the parsed standard time information to the laser radar 1 to complete the timing of the laser radar 1; after the laser radar 1 is timed, the collected point cloud data frames are all affixed with standard timestamp information.

[0148] Then, the sensor timing unit in the time synchronization module is used to divide the pulse signal of the differential crystal oscillator to generate an electrical signal of a certain frequency as the trigger acquisition signal of the hyperspectral camera 2. When the hyperspectral camera 2 receives the signal and detects the rising edge, data acquisition is performed; at the same time, the sensor timing unit also monitors the pulse information at all times. Based on the time information provided by the high-precision time unit, when the rising edge of the pulse signal is detected, the corresponding timestamp is affixed to the hyperspectral camera data to complete the timing of the hyperspectral camera 2.

[0149] Specifically, the timing and data acquisition methods of the visible light camera 3 and the thermal infrared camera 4 are similar to those of the hyperspectral camera 2 .

[0150] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-source aerial remote sensing data acquisition device, characterized in that: include: A flight platform and airborne equipment installed on the flight platform; The airborne equipment includes: multi-sensor ultra-compact integrated equipment, airborne integrated synchronous control equipment, and GNSS receiving antenna. The multi-sensor ultra-compact integrated equipment and the airborne integrated synchronous control equipment are connected by cables, and the GNSS receiving antenna is set on the end face of the flight platform; Multi-sensor ultra-compact integrated device for collecting multi-source remote sensing data; Airborne integrated synchronization control equipment, used to control the operation of multi-sensor ultra-compact integrated equipment; GNSS receiving antennas, which convert radio signals transmitted by satellites into electrical current for use by receiver electronics; The multi-sensor ultra-compact integrated device includes: a laser radar (1), a hyperspectral camera (2), a visible light camera (3), a thermal infrared camera (4), an inertial measurement unit (IMU) (5) and a reference mounting plate (6); The reference mounting plate (6) is provided with mounting reference edges for various sensors, and is used to provide mounting reference structures for various types of sensors; The laser radar (1), the visible light camera (3) and the thermal infrared camera (4) are all mounted on the lower end of the reference mounting plate (6); The hyperspectral camera (2) and the inertial measurement unit (IMU) (5) are mounted on the upper end of the reference mounting plate (6); The multi-type sensor ultra-compact integrated device is composed of multi-type remote sensing sensors in an upper and lower layered structure, which are rigidly connected and assembled through a reference mounting plate (6).

2. A multi-source aerial remote sensing data acquisition device according to claim 1, characterized in that: The reference mounting plate (6) is further provided with a tail support (7), a bottom mounting frame (8), a top mounting frame (9), and a plurality of shock absorbers (10); wherein, The tail support (7) is arranged on the lower end surface of the reference mounting plate (6) and is fixed to one side of the laser radar (1) by means of bolts; The bottom mounting frame (8) is arranged on the lower end surface of the reference mounting plate (6) and is fixed to the corresponding side of the laser radar (1) and the tail support (7) by bolts, and the visible light camera (3) and the thermal infrared camera (4) are both fixedly connected to the bottom mounting frame (8) by bolts; The top mounting bracket (9) is arranged on the upper end surface of the reference mounting plate (6) and is fixedly connected to the hyperspectral camera (2) via bolts; A plurality of shock absorbers (10) are provided, all of which are arranged at the lower end of the reference mounting plate (6) and are respectively located at the four corners of the reference mounting plate (6). The shock absorbers (10) are fixedly connected to the reference mounting plate (6) by bolts to reduce the influence of platform vibration on each sensor during flight.

3. The multi-source aerial remote sensing data acquisition device according to claim 1, characterized in that: The airborne integrated synchronous control equipment includes: an industrial control host (17), an integrated power supply and distribution module (18), a combined navigation host (19), a telescopic control console (20), a display (21), an aviation shock-absorbing cabinet (22), and a data storage unit (23); wherein, An aviation shock-absorbing cabinet (22) for integrating an industrial control host (17), an integrated power supply and distribution module (18), a combined navigation host (19), a telescopic control console (20), a display (21) and a data storage unit (23); The industrial control host (17), the integrated power supply and distribution module (18), and the data storage unit (23) are all arranged inside the aviation shock-absorbing cabinet (22) and are fixedly connected to the aviation shock-absorbing cabinet (22) by bolts; The industrial control host (17) is used to issue instructions to each functional module, control the power supply, acquisition, and storage working status of each sensor, and set the working parameters of each sensor; the integrated power supply and distribution module (18) is used to convert the power supply voltage of the flight platform to meet the power demand of each sensor; the data storage unit (23) is used to store the laser point cloud, hyperspectral image, thermal infrared image and visible light image data generated during the data acquisition process; One end of the telescopic control console (20) is embedded in the aviation shock-absorbing cabinet (22) away from the data storage unit (23), and the other side of the telescopic control console (20) can be extended out of the aviation shock-absorbing cabinet (22). The telescopic control console (20) is used to manually operate the industrial control host (17) equipment; The integrated navigation host (19) is arranged on the aviation shock-absorbing cabinet (22) and on the same side as the telescopic control console (20), and is fixedly connected to the aviation shock-absorbing cabinet (22) by bolts. The integrated navigation host (19) is used to receive and fuse measurement data from a global navigation satellite system and an inertial measurement unit (IMU) (5) to obtain three-dimensional position, velocity and attitude information; The display (21) is arranged on the aviation shock-absorbing cabinet (22) and on the same side as the telescopic console (20), and is located above the telescopic console (20). The display (21) is fixedly connected to the aviation shock-absorbing cabinet (22) by bolts and is used to display the working parameters of each device and to display the working status and data acquisition quality of each sensor in real time during operation.

4. A multi-source aerial remote sensing data acquisition system, comprising the multi-source aerial remote sensing data acquisition device according to any one of claims 1 to 3, further comprising: Power supply and distribution subsystem, integrated control subsystem, large-capacity data high-speed storage subsystem and real-time display and monitoring subsystem; among them, Power supply and distribution electronic system, used to distribute power supply that meets voltage and power requirements to various sensors and other electrical equipment; The integrated control subsystem is used to issue control instructions, centrally control multiple sensors for data collection, storage, and display operations, and ensure the synchronization of the time of each sensor; Large-capacity, high-speed data storage subsystem to meet the storage requirements of large data volumes and high data rates of multiple sensors; The real-time display and monitoring subsystem is used to display the data obtained by each sensor in real time during the operation process and monitor the working status parameters of the sensor.

5. A multi-source aerial remote sensing data acquisition system according to claim 4, characterized in that: The power supply and distribution subsystem includes isolated DC / DC modules and rack-mounted inverters; The isolated DC / DC module is used to convert the voltage of the DC power provided by the flight platform; The rack-mounted inverter is used to convert DC power into AC power. The DC voltage input by the isolated DC / DC module is converted into AC voltage; The integrated control subsystem includes a time synchronization module and a multi-sensor synchronization control module; The time synchronization module includes a high-precision time unit and a sensor timing unit, which are used to establish a high-precision time reference; The multi-sensor synchronization control module is used to comprehensively control multiple sensors for data acquisition, storage and display operations.

6. A multi-source aerial remote sensing data acquisition system according to claim 4, characterized in that: The high-capacity, high-speed data storage subsystem consists of Oculink connectors and disk arrays, and is used to store data collected by multiple sensors on board in real time. Among them, the Oculink connector is used to connect the disk array to the integrated control subsystem and perform PCIE4.0 connection between the disk array and the integrated control subsystem; The disk array is composed of a first solid-state hard drive, a second solid-state hard drive, and a third solid-state hard drive. The first solid-state hard drive is used to store laser point cloud data and thermal infrared image data, the second solid-state hard drive is used to store visible light image data, and the third solid-state hard drive is used to store hyperspectral image data and attitude position measurement data. The real-time display and monitoring subsystem includes a data analysis module and a data quick view module; The data parsing module is used to parse multiple types of data and perform quick image preprocessing; The data quick view module is used to scroll, refresh, and change the view of the generated graph in different quick view modes.

7. A multi-source aerial remote sensing data acquisition and control method, characterized in that: A multi-source aerial remote sensing data acquisition system according to any one of claims 4 to 6, comprising the following steps: S1. Connect the power line, trigger line, and data line of each sensor and power on the device; S2. Perform multi-sensor integrated control through the host computer control software in the integrated control subsystem, configure the parameters of each sensor, set the width and period of the trigger pulse, and transmit the setting instructions to the main control circuit board; S3. Start the operation and data collection of each sensor with one click manually, obtain the calibration parameters after the sensor calibration flight, and then synchronously collect and store the aerial remote sensing data; S4. During the acquisition process, the key parameters and operating status of each sensor are displayed in real time, and the data collected by each sensor is quickly displayed. After the task is completed, the operation of the sensor and data acquisition can be terminated with one click.

8. The multi-source aerial remote sensing data acquisition and control method according to claim 7, characterized in that: The sensor calibration in S3 is as follows: S31, selecting and laying out a calibration field, wherein the calibration field has buildings for laser radar (1) calibration and the ground features have reflectivity; S32. Set up the inspection and calibration route, adopt the vertical cross and large lateral overlap laying method, and evenly distribute multiple control points along the route direction; S33. Fly according to the set calibration route and collect lidar point cloud data; S34, automatically extract the connecting surface between the overlapping flight strips and obtain the centroid coordinates (X 84 , Y 84 , Z 84 ); S35, using the center-of-gravity coordinates as the connection points of different flight paths, and then establishing an error equation based on the difference between the center-of-gravity coordinates of the connection surface and the observation equation of the laser foot point; S36. Suppose there are N connection points, establish N error equations, and apply the least squares principle to solve the installation angle error.

9. The multi-source aerial remote sensing data acquisition and control method according to claim 7, characterized in that: The specific steps for synchronously collecting and storing aerial remote sensing data in S3 are: S331: establishing a time reference based on the GNSS information and the differential crystal oscillator provided by the integrated navigation host (19); S332: Calibrate the measurement time of the inertial measurement unit IMU (5) using the 1PPS signal sent by the integrated navigation host (19); S333: Using an improved Kalman filter algorithm to reduce the GNSS observation data delay and the inertial measurement unit (IMU) (5) data update calculation delay; S334: The sensor timing unit is used to perform timing on the laser radar (1), the hyperspectral camera (2), the visible light camera (3) and the thermal infrared camera (4), respectively, and to complete the synchronous acquisition of multi-source aerial remote sensing data.

10. The multi-source aerial remote sensing data acquisition and control method according to claim 9, characterized in that: The specific contents of S333 are: The first step is to save the output values ​​of the IMU accelerometer and gyroscope when the integrated navigation host (19) starts sampling the GNSS signal, and start calculating and updating the attitude, velocity and position of the current flight platform in real time when the GNSS observation data is actually received; First, the attitude differential equation is used to solve the attitude: and And use the formula to perform t k-1 Time to t k The attitude matrix update at this moment: Among them, b represents the flight platform coordinate system, i represents the inertial coordinate system, n represents the navigation coordinate system, and the matrix is the attitude relationship of the b system relative to the i system expressed by quaternions, represent Differentiation with respect to time, represent Differentiation with respect to time, Represents the projection of the angular velocity of system i relative to system n in system n, Represents the projection of the angular velocity of system n relative to system i in system n, Represents the attitude transformation matrix from the inertial coordinate system to the navigation coordinate system, Represents the direct output of the IMU, which is the projection of the angular velocity of the b system relative to the i system in the b system. It means that when the i system is used as the reference, the b system starts from t k-1 Time to t k The rotation changes of the moment, Depend on Sure, Represents in t k The attitude transformation matrix from the flight platform coordinate system to the inertial coordinate system at any moment, Represents in t k-1 The attitude transformation matrix from the flight platform coordinate system to the inertial coordinate system at any moment, Represents t k The attitude conversion matrix from the inertial coordinate system to the navigation coordinate system at the moment, Represents n series from t k-1 Time to t k The rotation changes of the moment, Represents t k-1 The attitude transformation matrix from the inertial coordinate system to the navigation coordinate system at any moment; Then, the velocity differential equation is used to update the velocity state and the integral is obtained: in, t k-1 The speed of time, is the n-system specific force velocity increment, is the velocity increment of harmful acceleration, t k the speed of the moment; Finally, the position update calculation is performed using the position differential equation: Among them, P k t k The position state matrix at the moment, is the IMU at t k The speed value output at each moment, is the transformation matrix, P k-1 t k-1 The position state matrix at the moment, t k-1 The speed value output at the moment, ΔT is the time increment; The second step is to first calculate the GNSS sampling time, i.e., t k The state parameter estimator and state parameter covariance estimator at the moment are then transferred to the current moment, that is, the update calculation is completed, t j At time j>k, the state transition is performed using the following formula to correct the delay error at the current moment: in, According to t k to t j k observation vector value pairs at time t j The state parameter vector X at the moment j The linear minimum variance estimate made, Φ j / k is the state transition matrix, t k The state parameter vector X at the moment k The updated estimate of is the covariance matrix of the forecast error, is the covariance matrix of the state parameters, is the transpose of the state transfer matrix, M j,k+1 is the correction matrix factor.

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