A method and device for real-time adjustment of range gate of satellite-borne photon counting laser altimeter

Abstract

The present invention discloses a method and device for real-time adjustment of the range gate of a satellite-borne photon counting laser altimeter, and belongs to the field of laser altimeter technology. The method comprises generating range gate position parameters using a coarse value of a priori ground position and a range threshold width of a system, and collecting echo data within the range gate; using an overlapping histogram algorithm to detect whether the echo data contains a surface echo signal: if a surface echo signal is detected, the position of the current surface echo signal is calculated using a centroid method; if no surface echo signal is detected, a sliding search, collection and detection of the surface echo signal based on the accuracy range of a priori ground value is performed; the surface echo signal detection result and the coarse value of the priori ground position are input into a Kalman filter to predict the position of the next surface echo signal. The present invention automatically captures and tracks terrain signals, predicts and adjusts the range gate position by real-time detection of photon altimeter data in a short period of time, thereby effectively acquiring terrain signals.

Description

Technical Field

[0001] The invention belongs to the technical field of laser altimetry, and in particular relates to a method and a device for real-time adjustment of a range gate of a satellite-borne photon counting laser altimeter. Background Art

[0002] As an advanced space measurement method, satellite-borne laser altimetry technology has been widely used in many fields such as geodesy, topographic mapping, ocean exploration, glacier monitoring and disaster assessment due to its significant advantages such as high precision, high resolution and the ability to quickly obtain large-area terrain information. This technology emits laser pulses to the target and accurately measures the time interval from the emission to the reception of the laser pulse, combined with the speed of light information, to achieve accurate measurement of the distance to the target, and then construct a three-dimensional terrain model of the target area.

[0003] At present, the core systems of satellite-borne laser altimetry technology mainly include full-waveform system and photon counting system. ICESat-2 is the world's only six-beam laser altimeter with a photon counting system. Since its operation in 2018, it has obtained a large amount of valuable data. As an emerging laser altimetry technology, the photon counting system has shown obvious advantages in many practical applications due to its high sensitivity and low energy requirements. Compared with full-waveform measurement, the photon counting system can collect echo signals with lower power consumption and higher sensitivity, and can more accurately capture weak target signals in complex environments. This makes the photon counting system have stronger anti-interference ability in complex environments, especially on ground targets with high reflection differences such as forest coverage and urban buildings, and can provide more accurate and complete terrain data.

[0004] However, a challenge facing the photon counting system is how to effectively manage a large amount of signal data. Since the echo signal of the laser altimeter system often has a huge amount of data when it is received, and the system's storage and processing capabilities are limited, an effective gating technology must be used to control the acquisition of data. The gating function mainly sets an appropriate receiving window to only receive photon data within a certain range gate (Range Gate, RG) near the ground signal, reducing the amount of unnecessary noise data, thereby alleviating the contradiction between the system storage resources and the large amount of noise data caused by single-photon sensitivity. Taking ICESat-2 as an example, it uses advanced receiving and processing algorithms. With the help of the global digital elevation model (DEM), global terrain model and surface type model pre-stored on the satellite, the signal processing algorithm effectively distinguishes the surface echo from the background noise, and only retains the data of a small vertical area near the surface position for telemetry, thereby greatly reducing the amount of storage and telemetry data. In view of the gating limitations existing in the current system, especially in a narrow range gating window, how to maximize the acquisition of target terrain signals has become a key research issue. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method and device for real-time adjustment of the range gate of a satellite-borne photon counting laser altimeter, which combines the coarse precision prior value to search for signals in real time, and realizes dynamic tracking and prediction of signals. By adjusting the position of the range gate in real time, the echo data near the terrain signal can be obtained to the greatest extent under limited gate conditions, thereby improving the ability of the photon counting laser altimeter to obtain terrain signals in complex environments, and improving measurement accuracy and system reliability.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for real-time adjustment of a range gate of a spaceborne photon counting laser altimeter, the method comprising:

[0008] Step 1: Generate range gate position parameters using the ground priori position rough value and the range threshold width of the system, and use the laser altimeter to continuously collect echo data within the range gate;

[0009] Step 2: Use the overlapping histogram algorithm to detect whether the collected echo data contains a surface echo signal: if a surface echo signal is detected, use the centroid method to calculate the position of the current surface echo signal; if no surface echo signal is detected, re-collect and detect the surface echo signal according to the rough value of the ground prior position and the position of the sliding range gate window of its error band until the surface echo signal is detected;

[0010] Step 3: Input the surface echo signal detection result and the rough value of the ground priori position into the Kalman filter to predict the position of the next surface echo signal.

[0011] Furthermore, the method also includes, if a surface echo signal interruption occurs, performing echo data collection and surface signal detection based on a rough value of the ground priori position and a sliding range gate window position of its error band, and after the surface signal is redetected, tracking the surface signal using the method in step 3.

[0012] Furthermore, the range gate position parameters in step 1 include the starting position and the ending position of the range gate, and the echo data are multiple distance values ​​from the laser altimeter to the ground within a preset time period.

[0013] Furthermore, if a surface signal is detected in step 2, calculating the position of the current surface signal using the centroid method includes:

[0014] Step 2.1, histogram the echo data within the range gate;

[0015] Step 2.2, set the merging step size and the overlap amount, merge and overlap the obtained histograms, and generate a new histogram;

[0016] Step 2.3, using the new histogram to calculate the detection threshold of the surface echo signal;

[0017] Step 2.4, traverse the new histogram to find out whether there is an interval greater than the detection threshold. If there are at least two intervals greater than the detection threshold, it means that there is a surface echo signal in the data; otherwise, there is no signal in the data but only noise;

[0018] Step 2.5: Calculate the centroid position of the surface echo signal, which is the current ground position.

[0019] Furthermore, the step 2.5 includes calculating the centroid positions of all intervals greater than the signal detection threshold, and performing weighted average calculation to obtain the centroid position of the surface echo signal.

[0020] Furthermore, if no surface signal is detected in step 2, collecting and detecting surface echo data for a preset time period according to the rough value of the ground priori position and the position of the sliding range gate window of its error band includes:

[0021] Step 2.6, defining the surface echo signal search area according to the priori rough value of the ground position and the error band;

[0022] Step 2.7, starting from the lowest search position of the error band, slide the surface echo signal position forward with a preset step length; until the maximum search position of the signal error band is reached or the surface echo signal is detected.

[0023] Furthermore, the step 3 comprises:

[0024] Step 3.1, establish the system state vector;

[0025] Step 3.2, predict the state vector estimate and error covariance of the next frame based on the target position estimate of the current frame according to the state transfer equation;

[0026] Step 3.3, calculate the Kalman gain coefficient using the error covariance and the covariance of the prior rough value;

[0027] Step 3.4, update the estimated value and error covariance of the current frame according to the Kalman gain coefficient and the prior rough value at the current moment;

[0028] Step 3.5: After the iteration is completed, the range gate position of the next acquisition frame is obtained, and the real-time position result is fed back to the altimeter receiver system.

[0029] In another aspect, the present invention provides a device for real-time adjustment of a range gate of a satellite-borne photon counting laser altimeter, comprising:

[0030] A data acquisition unit, used to generate range gate position parameters using a priori ground position rough value and a range threshold width of the system, and to continuously acquire echo data within the range gate using a laser altimeter;

[0031] The detection unit is used to detect whether the collected echo data contains a surface echo signal by using an overlapping histogram algorithm: if a surface echo signal is detected, the position of the current surface echo signal is calculated by using a centroid method; if no surface echo signal is detected, the surface echo signal is collected and detected again according to a rough value of the ground prior position and a sliding range gate window position of its error band until a surface echo signal is detected;

[0032] The prediction unit is used to input the surface echo signal detection result and the ground priori position rough value into the Kalman filter to predict the position of the next surface echo signal.

[0033] In a third aspect, the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for real-time adjustment of the range gate of a satellite-borne photon counting laser altimeter.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the aforementioned method for real-time adjustment of a range gate of a satellite-borne photon counting laser altimeter.

[0035] The beneficial effects of the present invention are:

[0036] The present invention combines prior information, real-time signal detection, Kalman filtering and sliding window search to adjust the position of the range gate in real time to accurately control the position of data collection. It can collect ground signals to the greatest extent when the system receiver resources are limited, adapt to certain terrain fluctuations, and improve the applicability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of a method for real-time adjustment of a range gate of a space-borne photon counting laser altimeter according to the present invention;

[0038] Figure 2 is a real topographic data map of the test area in the embodiment;

[0039] Figure 3 is a data diagram of a signal detection unit in the embodiment;

[0040] Figure 4 This is a result diagram of tracking terrain undulation changes in the embodiment. DETAILED DESCRIPTION

[0041] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0042] The present invention provides a method for real-time adjustment of the range gate of a satellite-borne photon counting laser altimeter. First, a range gate position is generated according to a priori rough value of the position of the surface signal, and the first echo data is collected. After a certain period of collection, a data unit for detection is generated. The overlapping histogram algorithm is used to detect whether the photon echo in the unit has surface signal data. If so, the center of gravity position of the current surface signal is output. Then, Kalman estimation is performed with the priori rough value of the ground position to predict the surface signal position of the next collection unit, and the surface signal position is fed back to the receiver system for real-time range gate adjustment. If no surface signal is detected, the range gate window position is slid with a certain step size according to the rough value accuracy range to search for surface signals. If a signal interruption occurs after signal tracking, the priori rough value is used again to search for signals. Specifically, the method includes:

[0043] Step 1: Based on the prior position rough value of the surface signal and the distance threshold width of the system Generates a range gate position, including the start position of the range gate and end position , for the first data collection.

[0044] ,

[0045] Since the photon counting laser altimeter system needs to accumulate data through high-repetition-rate laser emission, a certain amount of acquisition time is required. Collect echo data within the range gate. Finally, obtain a The laser altimeter reaches the ground within a certain time A set of distance values , where the i-th distance value The data will be used as a signal detection unit, also called a frame, for subsequent signal detection;

[0046] Step 2: Use the overlapping histogram algorithm to calculate the distance value set in the above signal detection unit Detect the surface signal and estimate the position of the surface signal. For the photon counting laser altimeter, the ranging value is composed of background noise and surface signal. The background noise is evenly distributed throughout the ranging range of the laser altimeter, and its amount depends on solar radiation, atmospheric scattering, and geographical environment. Generally, the solar radiation intensity is high during the day, and the background noise caused is at least one order of magnitude higher than that at night. The specific steps of the overlapping histogram algorithm are as follows:

[0047] Step 2.1: Distance value set Perform histogram processing. With a smaller interval width Partition distance value set , we can get Intervals:

[0048] ,

[0049] Each distance value Assign to the corresponding interval according to its size middle, It is The lower limit of the intervals, calculate the frequency of each interval ;

[0050] ,

[0051] in, is the indicator function, when the i-th distance value Falling in the range If it is within, it is equal to 1, otherwise it is equal to 0. In this way, the distance value set is obtained Histogram of .

[0052] Step 2.2: Histogram Merge overlaps to generate a new histogram The core idea is to merge the values ​​of adjacent intervals in the original histogram. The merged adjacent intervals have a certain degree of overlap, so as to obtain a smoother histogram to adapt to the characteristics of data distribution across intervals caused by terrain slope. Compared with the classic histogram statistical method, it can adapt to a certain terrain slope, and the algorithm is simple and effective and suitable for on-chip system implementation. Specifically, set the merging step size and overlap , then the new histogram The number of intervals :

[0053] ,

[0054] For the new histogram Each interval of The frequency calculation method is as follows:

[0055] ,

[0056] The first part is the front interval, the second part is the latter After merging, there is Through the above processing, we get a new histogram .

[0057] Step 2.3: Using the new histogram Calculate the detection threshold of the surface echo signal. Find the maximum interval value , calculate the mean of the remaining intervals except the maximum interval value :

[0058] ,

[0059] According to the mean Calculating the signal detection threshold :

[0060] ,

[0061] in, is a constant used to adjust the sensitivity of the threshold.

[0062] Step 2.4: Traverse the new histogram , check whether there is a signal greater than the signal detection threshold If there are at least two intervals that are greater than the signal detection threshold, it means that there are surface echo signals in the data; otherwise, there is no surface echo signal in the data, only noise.

[0063] Step 2.5: Calculate the centroid position of the surface echo signal That is the position of the surface in the current frame. Calculate the centroid position of all intervals greater than the signal detection threshold, and obtain the centroid position of the surface echo signal after weighted average calculation:

[0064] ,

[0065] in, Is a histogram The interval in The central location Is an indicator function, indicating that it is greater than the signal detection threshold interval.

[0066] If no surface signal is detected, the sliding range gate window method is used to search within the error band until the surface signal is found or the maximum position of the surface signal error band is reached. The prior rough value position of the known surface signal is The error band size is , the distance threshold width of the receiver system is .

[0067] Step 2.6: Based on the prior rough value position and error band of the surface signal, first define the surface signal search area as ;

[0068] Step 2.7: Search from the lowest position of the error band Start with Slide the signal position forward with the step length until the maximum search position of the signal error band is reached or the signal is detected. That is:

[0069] ,

[0070] Among them, the step length , which is the width of a distance threshold.

[0071] Step 3: After the surface signal is detected, the Kalman filter is used to estimate the accurate position of the surface signal estimated in the previous step and the prior rough value to predict the position of the surface signal in the next frame. Kalman filtering is a commonly used state estimation method that can be used to fuse information from multiple data sources to obtain a more accurate estimate. In this measurement system, the signal position result detected in the current frame can be As the state of the system, the rough precision values ​​provided by other systems are used as observation values, and the range gate position of the next frame is predicted through the Kalman filter algorithm. Specifically,

[0072] Step 3.1: Establish system state vector ,in Indicates The distance from the satellite-borne laser altimeter to the ground, Represents the rate of change of distance (related to terrain undulation and platform trajectory). The state transfer equation is as follows:

[0073] ,

[0074] ,

[0075] in, is the time interval between two consecutive data collections, is process noise, with mean 0 and variance The Gaussian distribution of , Represents the state transfer matrix of the system, specifically the uniform linear motion model. Process noise reflects the influence of unmodeled factors in the system, such as the jitter of the platform and the subtle interference of atmospheric environment changes on the laser.

[0076] Observation equation for a priori rough value as follows:

[0077] ,

[0078] ,

[0079] in, is the observation noise, with mean 0 and covariance The Gaussian distribution of , The relationship matrix between the observed value and the system state quantity is the measurement matrix. The observation noise mainly comes from the measurement error of the external measurement system itself, such as instrument accuracy limitation, electronic noise, etc.

[0080] Step 3.2: Prediction step. Use the surface signal position detection value of the current frame according to the state transfer equation Predict the estimated value of the state quantity for the next frame and error covariance :

[0081] ,

[0082] ,

[0083] ,

[0084] in, is the covariance of the process noise and T denotes the transpose.

[0085] Step 3.3, calculate the Kalman gain. Use the error covariance and the covariance of the prior rough value Calculate the Kalman gain coefficient .in Reflects the accuracy level of the prior rough value.

[0086] ,

[0087] Step 3.4: Based on the Kalman gain and the coarse-precision observation value Recalculate the estimate for the next frame and error covariance .

[0088] ,

[0089] Step 3.5: After the iteration is completed, the range gate position of the next acquisition frame is finally obtained, and the real-time position information is fed back to the altimeter receiver system.

[0090] Furthermore, during the execution of the entire method, if the surface signal is interrupted, echo data collection and surface signal detection are performed based on the rough value of the ground prior position and the sliding range gate window position of its error band. After the surface signal is redetected, the surface signal is tracked using the method in step 3.

[0091] Example

[0092] The range gate width of the satellite-borne photon counting laser altimeter system is set to 1000m, the laser repetition rate is set to 1000Hz, the prior rough value is provided by the orbit prediction value of the platform, and the error range is ±2km. In order to verify the effectiveness of the method of the present invention, a laser altimeter simulation data across a mountain range is generated according to the satellite orbit. Figure 2 It is the actual terrain data of the test area. The horizontal axis represents the along-track distance of the satellite, and the vertical axis represents the terrain height data.

[0093] The steps include:

[0094] Step 1: Use the prior coarse value to generate an initial range gate parameter and collect a data detection frame with a data width of 1000m and a collection duration of 100ms. During the collection process, assume that the system's ground signal detection probability is 0.6 and the background noise intensity is 1000KHz. The collected data with and without signals are as follows: Figure 3 As shown, the left picture shows the data with the collected signal, and the right picture shows the data with no signal and only noise.

[0095] Step 2: Use overlapping histograms to perform signal detection on the data containing the signal.

[0096] Step 2.1, first use a histogram interval of 10m to histogram the ranging data;

[0097] Step 2.2, merge the histograms with a step size of 6 to generate a new histogram;

[0098] Step 2.3, detect the maximum value in the new histogram frequency, calculate the mean of the remaining intervals except the maximum, and obtain the signal detection threshold;

[0099] Step 2.4, find out whether there are at least two intervals in the new histogram that are greater than the signal detection threshold. If so, the data contains a signal, otherwise there is no surface signal in the data;

[0100] Step 2.5: If the data contains a signal, calculate the center of gravity of the signal. Figure 3 The left figure shows the position of the signal gravity center detected in this embodiment. The data gravity center position of the surface signal is located at the horizontal line 307.238m;

[0101] Step 2.6: If there is no surface signal in the current data frame, define a surface signal search area;

[0102] Step 2.7: Use the sliding window method to search within the error band of ±2 km.

[0103] Step 3: Based on the detected surface signal, a Kalman filter is used in combination with a priori coarse values ​​to estimate the gate position of the next acquisition unit. Figure 4The figure shows the result of using a Kalman filter to detect and filter the real-time surface signal position of the test area data to guide the system to adjust the range gate position in real time to track the changes in terrain undulations.

[0104] On the other hand, the present invention provides a real-time adjustment device for a range gate of a space-borne photon counting laser altimeter, and each module included in the device can implement each step of the aforementioned method, specifically including:

[0105] A data acquisition unit, used to generate range gate position parameters using a rough ground a priori position value or a real-time predicted ground position value and a range threshold width of the system, and to continuously acquire echo data within the range gate using a laser altimeter;

[0106] The detection unit is used to detect whether the collected echo data contains a surface echo signal by using an overlapping histogram algorithm: if a surface echo signal is detected, the position of the current surface echo signal is calculated by using a centroid method; if no surface echo signal is detected, the surface echo signal is collected and detected according to a rough value of the ground prior position and a sliding range gate window position of the error band;

[0107] The prediction unit is used to input the surface echo signal detection result and the ground priori position rough value into the Kalman filter to predict the position of the next surface echo signal.

[0108] In a third aspect, the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for real-time adjustment of the range gate of a satellite-borne photon counting laser altimeter.

[0109] In a fourth aspect, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the aforementioned method for real-time adjustment of a range gate of a satellite-borne photon counting laser altimeter.

[0110] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for real-time adjustment of the range gate of a spaceborne photon counting laser altimeter, characterized in that: The method comprises: Step 1: Generate range gate position parameters using the ground priori position rough value and the range threshold width of the system, and use the laser altimeter to continuously collect echo data within the range gate; Step 2: Use the overlapping histogram algorithm to detect whether the collected echo data contains a surface echo signal: If a surface echo signal is detected, use the centroid method to calculate the position of the current surface echo signal; including: Step 2.1, histogram the echo data within the range gate; Step 2.2, set the merging step size and the overlap amount, merge and overlap the obtained histograms, and generate a new histogram; Step 2.3, using the new histogram to calculate the detection threshold of the surface echo signal; Step 2.4, traverse the new histogram to find out whether there is an interval greater than the detection threshold. If there are at least two intervals greater than the detection threshold, it means that there is a surface echo signal in the data; otherwise, there is no signal in the data but only noise; Step 2.5, calculate the centroid position of the surface echo signal as the current ground position; If no surface echo signal is detected, the surface echo signal is collected and detected again according to the rough value of the ground prior position and the sliding range gate window position of its error band until the surface echo signal is detected; including: Step 2.6, defining the surface echo signal search area according to the priori rough value of the ground position and the error band; Step 2.7, starting from the lowest search position of the error band, slide the surface echo signal position forward with a preset step length; until the maximum search position of the signal error band is reached or the surface echo signal is detected; Step 3: Input the surface echo signal detection result and the rough value of the ground priori position into the Kalman filter to predict the position of the next surface echo signal.

2. The method for real-time adjustment of the range gate of a spaceborne photon counting laser altimeter according to claim 1, characterized in that: The method also includes, if a surface echo signal interruption occurs, performing echo data acquisition and surface signal detection based on a rough value of the ground priori position and a sliding range gate window position of its error band, and tracking the surface signal using the method in step 3 after the surface signal is redetected.

3. The method for real-time adjustment of the range gate of a spaceborne photon counting laser altimeter according to claim 1, characterized in that: The range gate position parameters in step 1 include the starting position and the ending position of the range gate, and the echo data are multiple distance values ​​from the laser altimeter to the ground within a preset time period.

4. The method for real-time adjustment of the range gate of a spaceborne photon counting laser altimeter according to claim 1, characterized in that: The step 2.5 includes calculating the centroid positions of all intervals greater than the signal detection threshold, and obtaining the centroid position of the surface echo signal after performing weighted average calculation.

5. The method for real-time adjustment of the range gate of a spaceborne photon counting laser altimeter according to claim 1, characterized in that: The step 3 comprises: Step 3.1, establish the system state vector; Step 3.2, predict the state vector estimate and error covariance of the next frame based on the target position estimate of the current frame according to the state transfer equation; Step 3.3, calculate the Kalman gain coefficient using the error covariance and the covariance of the prior rough value; Step 3.4, update the estimated value and error covariance of the current frame according to the Kalman gain coefficient and the prior rough value at the current moment; Step 3.5: After the iteration is completed, the range gate position of the next acquisition frame is obtained, and the real-time position result is fed back to the altimeter receiver system.

6. A real-time adjustment device for range gate of a satellite-borne photon counting laser altimeter, characterized in that: include: A data acquisition unit, used to generate range gate position parameters using a priori ground position rough value and a range threshold width of the system, and to continuously acquire echo data within the range gate using a laser altimeter; The detection unit is used to detect whether the collected echo data contains a surface echo signal by using an overlapping histogram algorithm: if a surface echo signal is detected, the position of the current surface echo signal is calculated by using a centroid method; including: Perform histogram processing on the echo data within the range gate; Set the merging step size and the amount of overlap, merge and overlap the obtained histograms, and generate a new histogram; The detection threshold of the surface echo signal is calculated using the new histogram; Traverse the new histogram to find out whether there are intervals greater than the detection threshold. If there are at least two intervals greater than the detection threshold, it means that there are surface echo signals in the data; otherwise, there is no signal in the data, only noise; The calculated center of gravity of the surface echo signal is the current ground position; If no surface echo signal is detected, the surface echo signal is collected and detected again according to the rough value of the ground prior position and the position of the sliding range gate window of its error band until the surface echo signal is detected; Define the search area for the surface echo signal based on the prior rough value of the ground position and the error band; Starting from the lowest search position of the error band, slide the surface echo signal position forward with a preset step length; until the maximum search position of the signal error band is reached or the surface echo signal is detected; The prediction unit is used to input the surface echo signal detection result and the ground priori position rough value into the Kalman filter to predict the position of the next surface echo signal.

7. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; Wherein, when one or more programs are executed by the one or more processors, the one or more processors implement the real-time adjustment method of the range gate of a satellite-borne photon counting laser altimeter as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: Executable instructions are stored thereon, and when the instructions are executed by the processor, the processor can implement the real-time adjustment method of the range gate of a satellite-borne photon counting laser altimeter as described in any one of claims 1-5.

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