Infrared light intensity detection method and system

Abstract

The invention relates to the technical field of photoelectric detection, in particular to an infrared light intensity detection method and system, and the method comprises the following steps: calculating a pixel capacitor voltage and a time quotient value to obtain a time-varying rate, calculating a pixel fall amount according to the time-varying rate to construct a direction skewness proportion, judging the relation between the time-varying rate and a threshold value according to the proportion, and building a correction change rate; calculating the product of the width and the specific gravity to generate a correction amount, generating a light intensity remolding amount in combination with the change rate, and mapping the remolding amount to construct a spatial distribution matrix. According to the method, the time-varying rate is extracted by collecting pixel capacitor voltage quotient values to reveal underlying energy accumulation characteristics, the time-varying rate is extracted to calculate fall, a skewness specific gravity is constructed to capture a divergent asymmetric structure, and a variation rate is established according to specific gravity recombination logic to eliminate fixed network sensitivity defects. The correction is generated in combination with the skewness proportion expansion width, the change rate is fused to generate the remolding amount to comprehensively restore the real gradient diffusion attribute, and the position mapping remolding matrix is fused to break through the single expression limitation to reconstruct the spatial continuous distribution texture.

Description

Technical Field

[0001] This invention relates to the field of photoelectric detection technology, and in particular to an infrared light intensity detection method and system. Background Technology

[0002] The field of optoelectronic detection technology is an interdisciplinary field that integrates optics and electronics. Based on the photoelectric effect, it converts light signals into electrical signals through photoelectric detection devices, thereby extracting the physical characteristics of the target. This field mainly involves using optical elements such as lenses and filters to collect the target radiation beam, and then using sensors such as silicon-based photodiodes to convert the changes in the internal electronic transition states of the material induced by light irradiation into weak voltage or current changes. These changes are then converted into numerical quantities by preamplifier circuits and analog-to-digital conversion hardware for subsequent steps. Traditional infrared light intensity detection methods refer to the process of measuring the infrared radiation energy acquired by the receiving side of an infrared transceiver system. Traditional detection methods mainly rely on connecting an infrared receiving diode and a sampling resistor in series in the receiver circuit to convert the received infrared beam into an induced voltage, which is input to the non-inverting input of a hardware comparator. Simultaneously, a reference voltage provided by a fixed voltage divider resistor network is connected to the inverting input. The hardware comparator compares the difference in amplitude between the non-inverting and inverting inputs and outputs a corresponding high-level or low-level pulse switching signal.

[0003] Traditional infrared light intensity detection relies on a receiver circuit with a diode and a sampling resistor connected in series to convert the light beam into an induced voltage, which is input to the non-inverting input of a hardware comparator. The inverting input is connected to a fixed voltage divider network to provide a reference voltage. The amplitude difference between the two ends is compared to output a pulse flip signal. This operation mode, which relies on a fixed hardware threshold to compare the induced voltage, is highly susceptible to environmental radiation interference. The rigid voltage network is difficult to adapt to changes in the spatial distribution of light illumination, and a single pulse signal cannot reflect the true characteristics of the light spot energy diffusion. As a result, the detection accuracy of weak light signals in complex interference scenarios is limited, and the spatial resolution deviates from the original distribution state. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide an infrared light intensity detection method, comprising the following steps: S1: Collect the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, calculate the quotient of the output voltage value and the corresponding time length value of the basic integration time period, and obtain the voltage time-varying rate. S2: Based on the voltage time-varying rate, extract the voltage time-varying rate corresponding to the off-axis angle pixel, the right adjacent pixel, and the lower adjacent pixel of the infrared optical lens group, calculate the horizontal drop of the right adjacent pixel, calculate the vertical drop of the lower adjacent pixel, calculate the quotient of the horizontal drop and the vertical drop, and construct the directional skewness ratio. S3: Based on the directional skewness ratio, determine the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board. If the voltage time-varying rate is greater than the rated upper limit threshold, send a trigger level signal and calculate the quotient of the truncated instantaneous output voltage value and the trigger time length value. If the voltage time-varying rate is not greater than the rated upper limit threshold, retain the voltage time-varying rate and establish a corrected rate of change. S4: Calculate the product of the control terminal reference distribution width value and the directional skewness ratio to generate the skewness width correction amount, and calculate the product of the correction variation rate and the skewness width correction amount to generate the light intensity distribution reshaping amount; S5: Combining the row and column index values, perform matrix array position mapping on the light intensity distribution reshaping amount to construct a light intensity spatial distribution matrix.

[0005] As a further aspect of the present invention, the voltage time-varying rate includes photon accumulation rate, pixel response slope, and charge accumulation frequency; the directional skewness ratio includes spatial distortion parameters, energy defocusing characteristics, and asymmetric deformation index; the correction variation rate includes saturation suppression slope, dynamic exposure gradient, and anti-overflow calibration parameters; the light intensity distribution reshaping amount includes pixel equivalent radiance, Gaussian fitting amplitude, and distortion compensation brightness; and the light intensity spatial distribution matrix includes a full-field grayscale map, focal plane energy topology, and target intensity dot matrix.

[0006] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Collect the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, collect the corresponding time length value of the basic integration time period, aggregate the output voltage value and the time length value, extract the bit element sequence corresponding to the output voltage value and the time length value, combine the bit element sequence according to the row and column arrangement rules, and obtain the time and voltage parameter set. S102: Call the time and voltage parameter set, retrieve the output voltage value and the corresponding time length value of the basic integration time period, divide the output voltage value by the corresponding time length value of the basic integration time period, calculate the quotient of the output voltage value and the time length value, and perform sequence arrangement and recombination on the quotient according to the element node position index to obtain the voltage time-varying rate.

[0007] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Based on the voltage time-varying rate, extract the voltage time-varying rates corresponding to the off-axis angle pixels of the infrared optical lens group, the right adjacent pixels, and the bottom adjacent pixels. Retrieve the voltage time-varying rate of the off-axis angle pixels and the voltage time-varying rate of the right adjacent pixels. Subtract the voltage time-varying rate of the right adjacent pixels from the voltage time-varying rate of the off-axis angle pixels. Calculate the horizontal drop of the right adjacent pixels. Concatenate the horizontal drop with the full value and convert it into a one-dimensional array to establish a horizontal drop parameter set. S202: Call the horizontal drop parameter set, retrieve the voltage time-varying rate of the adjacent pixels below and the voltage time-varying rate of the off-axis angle pixels, subtract the voltage time-varying rate of the adjacent pixels below from the voltage time-varying rate of the off-axis angle pixels, calculate the vertical drop of the adjacent pixels below, pair the vertical drop with the horizontal drop parameter, extract the corresponding index node and construct a two-dimensional vector structure to obtain the orthogonal drop feature vector; S203: For the orthogonal drop feature vector, retrieve the horizontal drop and vertical drop, divide the horizontal drop by the vertical drop, calculate the corresponding numerical quotient of the horizontal drop and vertical drop, extract the node elements corresponding to the quotient, and perform spatial mapping arrangement in combination with the full distribution structure. Arrange the multidimensional data matrix according to the numerical row and column index priority rule, convert the internal mapping parameter node format, and generate the directional skewness ratio.

[0008] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Based on the directional skewness ratio, determine the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board. If the voltage time-varying rate is greater than the rated upper limit threshold inside the field programmable gate array board, send a trigger level signal, import the trigger level signal into the digital signal processing channel, perform signal frequency domain conversion and rearrangement, aggregate the output node state parameters in the channel, extract the channel link mapping parameters, and generate the over-limit trigger state quantity. S302: For the over-limit trigger state quantity, collect the value of the instantaneous output voltage and the value of the trigger time length, divide the value of the instantaneous output voltage by the value of the trigger time length, calculate the quotient of the instantaneous output voltage and the trigger time length, extract the underlying timing node element of the quotient, and perform spatial mapping arrangement of the timing node element according to the numerical row and column rules to obtain the transient truncation characterization quantity. S303: Based on the transient truncation characterization, detect the voltage time-varying rate and the rated upper limit threshold inside the field-programmable gate array board. If the voltage time-varying rate is not greater than the rated upper limit threshold inside the field-programmable gate array board, retain the voltage time-varying rate, fuse the retained voltage time-varying rate and the transient truncation characterization, merge the corresponding node numerical indexes, arrange the node vector sequence according to the time-series increment priority, and establish the corrected rate of change.

[0009] As a further aspect of the present invention, the discrete frequency band feature components of the trigger level signal are extracted, and the center frequency numerical parameter of the discrete frequency band feature components is identified. Following the rule of increasing center frequency numerical parameters, the positions of the discrete frequency band characteristic components are interchanged to generate a frequency domain transformation rearrangement sequence.

[0010] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: Call the directional skewness ratio, collect the control end reference distribution width value, perform a multiplication operation between the control end reference distribution width value and the directional skewness ratio, calculate the corresponding product between the control end reference distribution width value and the directional skewness ratio, extract the corresponding bottom-level mapping parameter node of the product, perform serialization arrangement on the parameter node according to the row and column encoding rules, construct the multi-dimensional feature parameter matrix shape, convert the internal element space rearrangement format, and generate the skewness width correction amount; S402: Using the skewness width correction amount, multiply the correction variation rate and the skewness width correction amount, calculate the corresponding product of the correction variation rate and the skewness width correction amount, capture the time-domain distribution feature vector associated with the product, perform discretization and dimensionality reduction mapping on the time-domain distribution feature vector according to the priority order of the element nodes, rearrange the internal hierarchical mapping format of the vector architecture, and obtain the light intensity distribution reshaping amount.

[0011] As a further aspect of the present invention, the node position coordinates of the parameter node are obtained, and the row interval step value and column interval step value contained in the row and column encoding rules are read. Based on the node position coordinates, row interval step size, and column interval step size, the parameter nodes are rearranged to establish a serialized parameter node set.

[0012] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: Based on the light intensity distribution reshaping amount and the row and column index values, capture the underlying data nodes inside the light intensity distribution reshaping amount, collect the corresponding pixel row and column index values, perform matching and combination operations on the pixel row and column index values ​​and the underlying data nodes, calculate the mapping sites associated with the pixel row and column index values ​​and the underlying data nodes, extract the discrete element sequence associated with the mapping sites, arrange the discrete element sequence according to the numerical encoding priority, and establish an array mapping parameter set. S502: Call the array mapping parameter set, retrieve the two-dimensional vector space representation architecture, retrieve the bottom element nodes inside the two-dimensional vector space representation architecture, perform row and column position offsets on the bottom element nodes, adjust the occupancy distribution state of the bottom element nodes in the global coordinate system, reorganize the topological hierarchy of the bottom element nodes according to the matrix form configuration specification, convert the multidimensional data hierarchy format of the global coordinate system, and obtain the light intensity spatial distribution matrix.

[0013] An infrared light intensity detection system, comprising: The time-varying rate extraction module collects the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, calculates the quotient of the output voltage value and the corresponding time length value of the basic integration time period, and obtains the voltage time-varying rate. The skewness weighting construction module extracts the voltage time-varying rates corresponding to the off-axis angle pixels, right adjacent pixels, and lower adjacent pixels of the infrared optical lens group according to the voltage time-varying rate, calculates the horizontal drop of the right adjacent pixels, calculates the vertical drop of the lower adjacent pixels, calculates the quotient of the horizontal drop and the vertical drop, and constructs the skewness weighting. The signal transmission module determines the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board based on the directional skewness ratio. If the voltage time-varying rate is greater than the rated upper limit threshold, a trigger level signal is sent, and the quotient of the truncated instantaneous output voltage value and the trigger time length value is calculated. If the voltage time-varying rate is not greater than the rated upper limit threshold, the voltage time-varying rate is retained, and a corrected rate of change is established. The skew width correction module calculates the product of the control terminal reference distribution width value and the directional skew ratio to generate the skew width correction amount, and calculates the product of the correction variation rate and the skew width correction amount to generate the light intensity distribution reshaping amount. The spatial distribution reconstruction module, in conjunction with the row and column index values, performs matrix array position mapping on the light intensity distribution reshaping amount to construct a light intensity spatial distribution matrix.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, time-varying rates are extracted by collecting pixel capacitance voltage and time quotient to reveal the dynamic characteristics of photon energy accumulation at the bottom layer. By extracting off-axis and adjacent pixel time-varying rates, bidirectional voltage drop is calculated to construct a skewed weight to capture the asymmetric physical structure of beam divergence. Based on the spatial skewed weight reorganization threshold decision logic, a correction rate is established to effectively eliminate the sensitivity defects of fixed network stray interference. The skewed weight is combined with the expansion of the reference width to generate a correction amount and the rate of variation is fused to generate a light intensity reshaping amount to fully restore the true gradient diffusion properties of the signal. The row and column position mapping is fused to reshape the light intensity matrix, completely breaking through the limitation of single pulse expression and thus accurately reconstructing the spatial continuous distribution texture of weak light field. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] Please see Figure 1 This invention provides an infrared light intensity detection method, comprising the following steps: S1: Collect the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, calculate the quotient of the output voltage value and the corresponding time length value of the basic integration time period, and obtain the voltage time-varying rate. S2: Based on the voltage time-varying rate, extract the voltage time-varying rates corresponding to the off-axis angle pixel, the right adjacent pixel, and the bottom adjacent pixel of the infrared optical lens group. Subtract the voltage time-varying rate corresponding to the off-axis angle pixel of the infrared optical lens group from the voltage time-varying rate corresponding to the right adjacent pixel to generate the horizontal drop. Subtract the voltage time-varying rate corresponding to the off-axis angle pixel of the infrared optical lens group from the voltage time-varying rate corresponding to the voltage time-varying rate of the bottom adjacent pixel to generate the vertical drop. Calculate the quotient of the horizontal drop and the vertical drop to construct the directional skewness ratio. S3: Based on the directional skewness ratio, determine the relationship between the voltage time-varying rate at the off-axis angle pixel position of the corresponding infrared optical lens group and the rated upper limit threshold inside the field programmable gate array board. If the voltage time-varying rate is greater than the rated upper limit threshold, send a trigger level signal to the gate pin of the reset field-effect transistor and record the trigger time length value. Calculate the quotient of the truncated instantaneous output voltage value and the trigger time length value. If the voltage time-varying rate is not greater than the rated upper limit threshold, retain the voltage time-varying rate and establish a corrected rate of change. S4: Calculate the product of the control end reference distribution width value and the directional skewness ratio to generate the skewness width correction amount, calculate the product of the correction variation rate and the skewness width correction amount to generate the light intensity distribution reshaping amount; S5: Extract the light intensity distribution reshaping amount and row and column index values ​​corresponding to the positions inside the infrared focal plane detector array, and perform matrix array position mapping on the light intensity distribution reshaping amount according to the row and column index values ​​to construct the light intensity spatial distribution matrix. Voltage time-varying rate includes photon accumulation rate, pixel response slope, and charge accumulation frequency; directional skewness ratio includes spatial distortion parameter, energy defocusing characteristic, and asymmetric deformation index; correction variation rate includes saturation suppression slope, dynamic exposure gradient, and anti-overflow calibration parameter; light intensity distribution reshaping amount includes pixel equivalent radiance value, Gaussian fitting amplitude, and distortion compensation brightness; light intensity spatial distribution matrix includes full field-of-view grayscale map, focal plane energy topology, and target intensity lattice.

[0020] Please see Figure 2 The specific steps of S1 are as follows: S101: Collect the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, collect the corresponding time length value of the basic integration time period, aggregate the output voltage value and the time length value, extract the bit element sequence corresponding to the output voltage value and the time length value, combine the bit element sequence according to the row and column arrangement rules, and obtain the time and voltage parameter set. The analog-to-digital conversion channel directly scans the level of the integrating capacitor pins (640 rows x 512 columns) within the infrared focal plane detector array, acquiring the output voltage value at the end of the basic integration time period. In practical applications, the basic integration time period is the time interval between the shutter synchronization signal trigger and the arrival of the charge transfer pulse, recorded by an internal high-frequency clock counter. The output voltage values ​​and corresponding time length values ​​of the 327,680 test pixel nodes are processed by storing adjacent values ​​at the underlying memory address, completing the value aggregation operation. The bit element sequences corresponding to the output voltage values ​​and time length values ​​within the aforementioned storage area are extracted and interleaved and reassembled according to the column-first, row-second numerical increment encoding rule. During sequence reassembly, null nodes containing invalid identifiers are removed, and a mean interpolation algorithm is used to fill in missing segments, ensuring the continuity of all sequence nodes. After filling, a set of time and voltage parameters, interwoven with time and voltage attributes, is obtained. To illustrate the specific operations of the above process, when the output voltage value of the pixel in the first row and first column is 2.5 volts, and the time length corresponding to the basic integration time period recorded by the counter is 500 microseconds, the 2.5 volts and 500 microseconds are aggregated in the memory register according to consecutive address segments. Then, the 32-bit binary floating-point sequence corresponding to 2.5 and the 16-bit integer sequence corresponding to 500 are extracted and merged into the parameter buffer according to the row and column arrangement rules of the first row and first column, forming the basic node data of the time and voltage parameter set. The above aggregation and arrangement operations are repeated for other pixels. This data acquisition and arrangement process avoids directly defining conversion formulas, but instead uses low-level memory address mapping combined with queue arrangement operation logic. Table 1 lists the parameter acquisition results of local pixel nodes within the array. Table 1: Initial Parameters for Pixel Nodes Cell row position index Cell column position index Integral terminal output voltage value Base time length value 1 1 2.5 500 1 2 2.6 500 1 3 2.4 500 2 1 2.7 500 As shown in Table 1, all extracted parameters were obtained through direct sampling of the physical channel, which objectively reflects the true charge response state of the pixel array at the end of the basic integration time period. The acquisition of time and voltage parameter sets lays a reliable data foundation for subsequent rate of change extrapolation.

[0021] S102: Call the time and voltage parameter set, retrieve the output voltage value and the corresponding time length value of the basic integration time period, divide the output voltage value by the corresponding time length value of the basic integration time period, calculate the quotient of the output voltage value and the time length value, and perform sequence arrangement and recombination on the quotient according to the element node position index to obtain the voltage time-varying rate. The microprocessor uses addressing instructions to retrieve the output voltage value and the corresponding time length of the basic integration time period for each pixel node. The retrieved output voltage value is used as the dividend, and the corresponding time length of the basic integration time period is used as the divisor to perform a division operation, calculating the quotient of the output voltage value and the time length. Taking the pixel in the first row and first column as an example, the retrieved output voltage value is 2.5 volts, and the corresponding time length of the basic integration time period is 500 microseconds. After converting 500 microseconds to the standard time unit of 0.0005 seconds, the above division operation is performed, dividing 2.5 volts by 0.0005 seconds, resulting in a quotient of 5000 volts per second. After obtaining the quotient values ​​of all pixel nodes, the quotient values ​​are sequentially rearranged according to the initial physical element node position index of the pixel in the 640x512 array. That is, the quotient values ​​from row 1, column 1 to row 512, column 640 are sequentially filled into a new 2D memory data block according to the matrix coordinate arrangement rules. In this process, the threshold for judging whether the quotient value belongs to the abnormal high-frequency noise range is set to 8000 volts per second. If the calculated quotient value exceeds 8000 volts per second, the quotient values ​​of the surrounding 8 adjacent nodes are summed and divided by 8 to calculate the mean value, which is then used to replace the original abnormal quotient value. The threshold of 8000 volts per second is derived from the statistical analysis of the highest time-varying rate of the previous 100 historical normal environmental samples, with an additional 10% redundancy, to obtain the voltage time-varying rate. The advantage of this operational logic is that, by combining direct division operations with precise reorganization of physical space indexes, a linear mapping between time-dimensional integration action and voltage change depth is established, eliminating readout deviations caused by differences in exposure time.

[0022] Please see Figure 3 The specific steps of S2 are as follows: S201: Based on the voltage time-varying rate, extract the voltage time-varying rate of the off-axis angle pixel, the right adjacent pixel, and the bottom adjacent pixel of the infrared optical lens group. Retrieve the voltage time-varying rate of the off-axis angle pixel and the voltage time-varying rate of the right adjacent pixel. Subtract the voltage time-varying rate of the right adjacent pixel from the voltage time-varying rate of the off-axis angle pixel. Calculate the horizontal drop of the right adjacent pixel. Concatenate the horizontal drop with the full value and convert it into a one-dimensional array to establish a horizontal drop parameter set. Using spatial coordinate positioning commands, the off-axis angle pixels of the infrared optical lens assembly, as well as the voltage time-varying rates of their right-hand and bottom adjacent pixels, are extracted. The voltage time-varying rate of the off-axis angle pixel located in row 10, column 20, and the voltage time-varying rate of its right-hand adjacent pixel located in row 10, column 21, are retrieved. The voltage time-varying rate of the off-axis angle pixel is used as the minuend, and the voltage time-varying rate of its right-hand adjacent pixel is used as the subtrahend to perform a subtraction operation, calculating the difference between these two horizontally adjacent nodes. This difference represents the horizontal drop of the right-hand adjacent pixel. For example, if the retrieved voltage time-varying rate of the off-axis angle pixel is 5000 volts per second, and the voltage time-varying rate of the right-hand adjacent pixel is 4800 volts per second, subtracting 4800 volts per second from 5000 volts per second yields a horizontal drop of 200 volts per second. Subsequently, the extraction and subtraction operations described above are repeatedly performed on all off-axis angular target nodes within the projection range of the entire lens group to obtain the horizontal drop value corresponding to each node. The obtained individual horizontal drop values ​​are then concatenated with the array's full base values ​​using the underlying data pointer in memory, and forcibly converted and merged into a continuous 1D array structure to establish the horizontal drop parameter set.

[0023] S202: Call the horizontal drop parameter set, retrieve the voltage time-varying rate of the adjacent cells below and the voltage time-varying rate of the off-axis angle cells, subtract the voltage time-varying rate of the adjacent cells below from the voltage time-varying rate of the off-axis angle cells, calculate the vertical drop of the adjacent cells below, perform pairing and combination of the vertical drop and the horizontal drop parameters, extract the corresponding index nodes and construct a two-dimensional vector structure to obtain the orthogonal drop feature vector; The addressing operation retrieves the voltage time-varying rate of the adjacent cell below (located in row 11, column 20) and the voltage time-varying rate of the off-axis angle cell (located in row 10, column 20). The off-axis angle cell voltage time-varying rate is used as the minuend, and the voltage time-varying rate of the adjacent cell below is used as the subtrahend to perform a subtraction operation, calculating the difference between these two vertically adjacent nodes, which is the vertical drop of the adjacent cell below. For example, if the voltage time-varying rate of the aforementioned off-axis angle cell is 5000 volts per second, and the voltage time-varying rate of the adjacent cell below is found to be 4900 volts per second, subtracting 4900 volts per second from 5000 volts per second yields a vertical drop of 100 volts per second. After obtaining the vertical drop, it is paired and combined with the horizontal drop parameter corresponding to the same off-axis angle coordinate node in the aforementioned horizontal drop parameter set. During the pairing process, the corresponding index node is extracted based on the physical absolute coordinates of the off-axis angle pixel. The horizontal drop is assigned to the first dimension of the vector, and the vertical drop is assigned to the second dimension, thus constructing an independent 2D vector structure. By combining the values ​​obtained from the previous example, the specific parameters of the generated 2D vector are the first value 200 and the second value 100, resulting in an orthogonal drop feature vector.

[0024] S203: For orthogonal drop feature vectors, retrieve horizontal drop and vertical drop, divide the horizontal drop by the vertical drop, calculate the corresponding numerical quotient of the horizontal drop and vertical drop, extract the node elements corresponding to the quotient, and perform spatial mapping arrangement in combination with the full distribution structure. Arrange the multidimensional data matrix form according to the numerical row and column index priority rule, convert the internal mapping parameter node format, and generate the directional skewness proportion. Using the horizontal drop as the dividend and the vertical drop as the divisor, a division operation is performed to calculate the quotient of the corresponding values. Using the values ​​from the previous example, with a horizontal drop of 200 and a vertical drop of 100, dividing 200 by 100 yields a quotient of 2. The original target pixel node element corresponding to this quotient is extracted and spatially mapped using the full distribution structure containing global position information. During this arrangement, all quotients are arranged in an increasing sequence according to the priority rule of row index as primary and column index as secondary, reconstructing a new multidimensional data matrix. Subsequently, the underlying format of each mapping parameter node within this matrix is ​​transformed, truncating and quantizing the original floating-point data into unsigned 16-bit integer data to generate directional skewness weights. Table 2 lists the skewness weight parameters generated by local calculations. Table 2: Local Directional Skewness Proportion Mapping Table Node row index Node column index Horizontal drop value Vertical drop value Directional skewness proportion results 10 20 200 100 2 10 21 180 60 3 11 20 150 150 1 11 21 240 60 4 Referring to Table 2, all directional skewness ratios were directly derived from the same-source drop data through division, eliminating dimensional interference. The advantage of this operational logic is that, through division ratios and spatial priority sorting operations, the main tilt direction of light intensity distortion in each pixel in the spatial structure is quantified.

[0025] Please see Figure 4 The specific steps of S3 are as follows: S301: Based on the directional skewness ratio, determine the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board. If the voltage time-varying rate is greater than the rated upper limit threshold inside the field programmable gate array board, send a trigger level signal, import the trigger level signal into the digital signal processing channel, perform signal frequency domain conversion and rearrangement, aggregate the output node state parameters in the channel, extract the channel link mapping parameters, and generate the over-limit trigger state quantity. In conjunction with the global voltage time-varying rate, a low-level comparator determines the relationship between the voltage time-varying rate of each pixel node and the preset upper limit threshold of the field-programmable gate array (FPGA) board. The specific setting of the upper limit threshold is based on the extreme test records of the infrared detector's background noise drift under room temperature standard blackbody radiation. The maximum time-varying rate from 500 consecutive tests is extracted as a basis and multiplied by a safety factor of 1.5 to determine the threshold. The actual calculation process is as follows: the recorded maximum time-varying rate is 4000 volts per second. Multiplying 4000 volts per second by 1.5 yields a rated upper limit threshold of 6000 volts per second. The voltage time-varying rate of the target node is then judged. If a node's voltage time-varying rate is found to be 7000 volts per second, since 7000 is greater than 6000, it is determined that the voltage time-varying rate exceeds the rated upper limit threshold of the FPGA board. At this point, the logic control unit sends a trigger level signal, i.e., outputs a 3.3-volt high-level pulse, and imports this trigger level signal into the digital signal processing channel via the hardware bus. Inside the channel, the Fast Fourier Transform (FFT) component is invoked to perform a signal frequency domain transformation and rearrangement operation, extracting 1024 consecutive sampling points in the time sequence as input, and converting this set of 1D time-domain signals into a frequency-domain sequence containing 512 frequency components. Subsequently, the current operating temperature, core frequency, and other status parameters of the output nodes within the processing channel are aggregated, and mapping parameters such as the rotation factor required for performing the Fourier transform in the channel link are extracted. These parameters are packaged and encapsulated into a data frame of a specific format to generate the over-limit trigger state quantity.

[0026] S302: For the over-limit trigger state quantity, collect the value of the instantaneous output voltage and the value of the trigger time length, divide the value of the instantaneous output voltage by the value of the trigger time length, calculate the quotient of the instantaneous output voltage and the trigger time length, extract the underlying timing node element of the quotient, and perform spatial mapping and arrangement of the timing node element according to the numerical row and column rules to obtain the transient truncation characterization quantity. By parsing the encapsulated data frame, the instantaneous output voltage value at the moment the state is triggered and the trigger time duration are collected. A division operation is performed using the instantaneous output voltage value as the dividend and the trigger time duration as the divisor to calculate the quotient. For example, if the instantaneous output voltage value is 3.0 volts and the trigger time duration is 300 microseconds, converting 300 microseconds to 0.0003 seconds and dividing 3.0 volts by 0.0003 seconds yields a quotient of 10,000 volts per second. After this division, the corresponding timing node element in the underlying memory register is extracted. This timing node element is then spatially mapped and arranged according to the row and column positions of the source pixel values ​​at the time of the trigger event, filling it into a coordinate position corresponding to a blank grid with the same resolution as the focal plane array. The extraction and spatial mapping operation is performed iteratively on all nodes that generate out-of-limit triggering state quantities during the scanning cycle. The positions of non-triggered nodes are filled with 0 to obtain the transient truncation characterization quantity.

[0027] S303: Based on the transient truncation characterization, detect the voltage time-varying rate and the rated upper limit threshold inside the field-programmable gate array board. If the voltage time-varying rate is not greater than the rated upper limit threshold inside the field-programmable gate array board, retain the voltage time-varying rate, fuse the retained voltage time-varying rate and the transient truncation characterization, merge the corresponding node numerical indexes, arrange the node vector sequence according to the time-series increment priority, and establish the corrected rate of change. The logic unit re-detects the voltage time-varying rate of all nodes globally and compares it with the rated upper limit threshold of 6000 volts per second set internally by the field-programmable gate array (FPGA) board. If the comparison finds that the voltage time-varying rate of a certain pixel node is 5000 volts per second, since 5000 is not greater than 6000, it is determined that the voltage time-varying rate is not greater than the rated upper limit threshold internally by the FPGA board. The original voltage time-varying rate value of that node is directly retained in memory through a latch instruction. Subsequently, a low-level data fusion operation is performed on the normal node set with retained voltage time-varying rates and the transient truncated representation quantity containing extreme quotient values. Specifically, the corresponding node value indices of the two in the array topology coordinate system are merged. For the same coordinate position, if there is a non-zero value in the transient truncated representation quantity, the original rate of change is overwritten; if it is 0, the retained voltage time-varying rate is used to fill it. After completing the above index and value merging, extract the final values ​​of all nodes in the entire graph, and perform sequence rearrangement on the nodes from earliest to latest according to the priority of their time-series increment changes on the time axis, that is, the order in which the occurrence rate values ​​change, to establish the corrected change rate.

[0028] Please see Figure 5 The specific steps of S4 are as follows: S401: Call the directional skewness ratio, collect the control end baseline distribution width value, perform a multiplication operation between the control end baseline distribution width value and the directional skewness ratio, calculate the corresponding product between the control end baseline distribution width value and the directional skewness ratio, extract the corresponding underlying mapping parameter node of the product, perform serialization and arrangement of the parameter node according to the row and column encoding rules, construct the multidimensional feature parameter matrix shape, convert the internal element space rearrangement format, and generate the skewness width correction amount; The reference width of the control terminal is acquired via a communication interface. This reference width is determined by the measured full width at half maximum (FWHM) constant of the lens's physical point spread function. With a focal length of 50 mm, the reference width is measured and calibrated using an optical interferometer, yielding a reference width of 15 micrometers (pixels). The acquired reference width value of 15 is multiplied by the directional skewness ratio value of 2 obtained in the 10th row, 20th column of the previous example, to calculate the product of the reference width and the directional skewness ratio. Multiplying 15 by 2 yields a product of 30. After performing this multiplication operation on all directional skewness ratios within the array, the mapping parameter nodes corresponding to each product result are extracted from the underlying storage medium. Following a row-column encoding rule that scans column by column from left to right and progresses row by row from top to bottom, the parameter nodes containing the product values ​​are serialized and pushed sequentially into a stack structure. Then, a multidimensional feature parameter matrix containing row and column dimensions is constructed, and through instruction-level calls, the spatial rearrangement format of each element in the matrix is ​​transformed, changing it from a linear queue to a grid structure strictly aligned with the infrared array, generating the skewness width correction.

[0029] S402: Using the skewness width correction amount, the correction variation rate and the skewness width correction amount are multiplied to calculate the corresponding product of the correction variation rate and the skewness width correction amount. The time-domain distribution feature vector associated with the product is captured. The time-domain distribution feature vector is discretized and dimension-reduced according to the priority order of the element nodes. The internal hierarchical mapping format of the vector architecture is rearranged to obtain the light intensity distribution reshaping amount. Before performing calculations, the 1D vector of the corrected rate of change is restored to a 2D matrix with the same size as the skewness width correction amount, based on row and column rules. Then, element-wise multiplication is performed on each node value in the corrected rate of change matrix with the corresponding physical coordinate node value in the skewness width correction amount matrix. For example, if a node has a corrected rate of change of 5000 and a corresponding skewness width correction amount of 30, multiplying 5000 by 30 yields a product of 150000. After performing all point-to-point multiplications on the entire image (640 x 512 pixels), these product results are captured and aggregated to construct a distribution feature vector set associated with temporal changes. This temporal distribution feature vector set is then sorted from largest to smallest according to the priority order of its element node values. Based on the sorting results, the full-precision floating-point values ​​of the top 1000 high-frequency, high-order feature nodes are retained, while truncation and rounding are performed on the remaining low-order nodes to achieve discretization and dimensionality reduction mapping, eliminating background redundant and weakly correlated terms. Finally, the internal hierarchy of the dimensionality-reduced vector architecture is rearranged, and its multi-dimensional deep features are transformed and mapped into a flattened single-level format to obtain the reshaped light intensity distribution.

[0030] Please see Figure 6 The specific steps of S5 are as follows: S501: Based on the light intensity distribution reshaping amount and row and column index values, capture the underlying data nodes inside the light intensity distribution reshaping amount, collect the corresponding pixel row and column index values, perform matching and combination operations on the pixel row and column index values ​​and the underlying data nodes, calculate the mapping position associated with the pixel row and column index values ​​and the underlying data nodes, extract the discrete element sequence associated with the mapping position, arrange the discrete element sequence according to the numerical encoding priority, and establish an array mapping parameter set. The kernel access instructions capture the underlying data nodes within the reshaped light intensity distribution after dimensionality reduction and filtering. Simultaneously, the absolute row and column indices of the corresponding pixels in the original 640x512 array are collected. The captured pixel row and column indices are then matched and combined with the corresponding underlying data nodes. This combination operation involves fusing the row, column, and reshaped values ​​into a single 64-bit composite integer code using a shift and concatenation instruction. For example, if the reshaped value of the node corresponding to row 10 and column 20 is 150000, a memory-level bitwise AND-OR operation is performed on 10, 20, and 150000 to calculate and lock the unique mapping point between the pixel row and column indices and the underlying data node. After concatenating all distribution nodes, the discrete element sequence associated with the mapping point is extracted. The discrete element sequence is arranged in ascending order of size, using the composite integer code generated by the aforementioned combination operation as the numerical encoding priority, thus establishing an array mapping parameter set that integrates coordinates and light intensity reshaped data.

[0031] S502: Call the array mapping parameter set, retrieve the two-dimensional vector space representation architecture, retrieve the bottom element nodes inside the two-dimensional vector space representation architecture, perform row and column position offsets on the bottom element nodes, adjust the occupancy distribution state of the bottom element nodes in the global coordinate system, reorganize the topological hierarchy of the bottom element nodes according to the matrix form configuration specification, convert the multidimensional data hierarchy format of the global coordinate system, and obtain the light intensity spatial distribution matrix. The associated 2D vector space representation architecture is retrieved, and the underlying element nodes within this architecture are called up. The row and column index values ​​contained in the composite encoding of each node are parsed. For each underlying element node, a row and column position offset operation is performed according to a preset lens distortion center offset constant. The specific setting of the above preset constant is based on the measured value of the optical axis center deviation at the time of detection at the factory. In this example, the row offset reference is set to positive 2 pixels, and the column offset reference is set to negative 1 pixel. For the aforementioned node in row 10 and column 20, its row value 10 is increased by 2 to become 12, and its column value 20 is decreased by 1 to become 19, thereby adjusting the actual occupancy distribution of this underlying element node within the entire 640 multiplied by 512 global coordinate system. Based on the newly calculated and updated coordinate distribution group, the topological hierarchy of the underlying element nodes is recombined according to the matrix configuration specification of the standard display buffer. The composite encoding encapsulation format of the data after position translation correction is stripped, the multi-dimensional data hierarchy format inside the global coordinate system is converted, and the pure reshaped light intensity data is filled back into the video output register according to the new coordinates to obtain the light intensity spatial distribution matrix. Table 3 shows the coordinate mapping relationship of local nodes before and after offset correction. Table 3: Spatial Distribution Offset Mapping Table of Light Intensity Initial row index Initial column index Light intensity distribution reshaping amount Offset after row index Offset column index 10 20 150000 12 19 10 21 148000 12 20 11 20 145000 13 19 As shown in Table 3, the offset of all coordinate nodes strictly follows the preset optical axis deviation constant for rigid translation calculation. The advantage of this calculation logic is that the pure arithmetic spatial offset achieved by addition and subtraction, combined with format decapsulation, completes the inverse compensation of hard distortion with extremely low overhead in the last buffer stage of video output.

[0032] Please see Figure 7 An infrared light intensity detection system, comprising: The time-varying rate extraction module collects the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, calculates the quotient of the output voltage value and the corresponding time length value of the basic integration time period, and obtains the voltage time-varying rate. The skewness weighting construction module extracts the voltage time-varying rates of the off-axis angle pixels, the right adjacent pixels, and the bottom adjacent pixels of the infrared optical lens group based on the voltage time-varying rate. It calculates the horizontal drop of the right adjacent pixels, the vertical drop of the bottom adjacent pixels, and the quotient of the horizontal drop and the vertical drop to construct the skewness weighting. The signal transmission module determines the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board based on the directional skew ratio. If the voltage time-varying rate is greater than the rated upper limit threshold, a trigger level signal is sent, and the quotient of the truncated instantaneous output voltage value and the trigger time length value is calculated. If the voltage time-varying rate is not greater than the rated upper limit threshold, the voltage time-varying rate is retained, and a corrected rate of change is established. The skewness width correction module calculates the product of the control end reference distribution width value and the directional skewness ratio to generate the skewness width correction amount, and calculates the product of the correction variation rate and the skewness width correction amount to generate the light intensity distribution reshaping amount. The spatial distribution reconstruction module, in conjunction with row and column index values, performs matrix array position mapping on the light intensity distribution reshaping amount to construct a light intensity spatial distribution matrix.

[0033] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of protection of the described technical solutions.

Claims

1. A method for detecting infrared light intensity, characterized in that, Includes the following steps: S1: Collect the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, calculate the quotient of the output voltage value and the corresponding time length value of the basic integration time period, and obtain the voltage time-varying rate. S2: Based on the voltage time-varying rate, extract the voltage time-varying rate corresponding to the off-axis angle pixel, the right adjacent pixel, and the lower adjacent pixel of the infrared optical lens group, calculate the horizontal drop of the right adjacent pixel, calculate the vertical drop of the lower adjacent pixel, calculate the quotient of the horizontal drop and the vertical drop, and construct the directional skewness ratio. S3: Based on the directional skewness ratio, determine the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board. If the voltage time-varying rate is greater than the rated upper limit threshold, send a trigger level signal and calculate the quotient of the truncated instantaneous output voltage value and the trigger time length value. If the voltage time-varying rate is not greater than the rated upper limit threshold, retain the voltage time-varying rate and establish a corrected rate of change. S4: Calculate the product of the control terminal reference distribution width value and the directional skewness ratio to generate the skewness width correction amount, and calculate the product of the correction variation rate and the skewness width correction amount to generate the light intensity distribution reshaping amount; S5: Combining the row and column index values, perform matrix array position mapping on the light intensity distribution reshaping amount to construct a light intensity spatial distribution matrix.

2. The infrared light intensity detection method according to claim 1, characterized in that, The voltage time-varying rate includes photon accumulation rate, pixel response slope, and charge accumulation frequency; the directional skewness ratio includes spatial distortion parameters, energy defocusing characteristics, and asymmetric deformation index; the correction variation rate includes saturation suppression slope, dynamic exposure gradient, and anti-overflow calibration parameters; the light intensity distribution reshaping amount includes pixel equivalent radiance, Gaussian fitting amplitude, and distortion compensation brightness; and the light intensity spatial distribution matrix includes a full-field grayscale spectrum, focal plane energy topology, and target intensity lattice.

3. The infrared light intensity detection method according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Collect the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, collect the corresponding time length value of the basic integration time period, aggregate the output voltage value and the time length value, extract the bit element sequence corresponding to the output voltage value and the time length value, combine the bit element sequence according to the row and column arrangement rules, and obtain the time and voltage parameter set. S102: Call the time and voltage parameter set, retrieve the output voltage value and the corresponding time length value of the basic integration time period, divide the output voltage value by the corresponding time length value of the basic integration time period, calculate the quotient of the output voltage value and the time length value, and perform sequence arrangement and recombination on the quotient according to the element node position index to obtain the voltage time-varying rate.

4. The infrared light intensity detection method according to claim 3, characterized in that, The specific steps of S2 are as follows: S201: Based on the voltage time-varying rate, extract the voltage time-varying rates corresponding to the off-axis angle pixels of the infrared optical lens group, the right adjacent pixels, and the bottom adjacent pixels. Retrieve the voltage time-varying rate of the off-axis angle pixels and the voltage time-varying rate of the right adjacent pixels. Subtract the voltage time-varying rate of the right adjacent pixels from the voltage time-varying rate of the off-axis angle pixels. Calculate the horizontal drop of the right adjacent pixels. Concatenate the horizontal drop with the full value and convert it into a one-dimensional array to establish a horizontal drop parameter set. S202: Call the horizontal drop parameter set, retrieve the voltage time-varying rate of the adjacent pixels below and the voltage time-varying rate of the off-axis angle pixels, subtract the voltage time-varying rate of the adjacent pixels below from the voltage time-varying rate of the off-axis angle pixels, calculate the vertical drop of the adjacent pixels below, pair the vertical drop with the horizontal drop parameter, extract the corresponding index node and construct a two-dimensional vector structure to obtain the orthogonal drop feature vector; S203: For the orthogonal drop feature vector, retrieve the horizontal drop and vertical drop, divide the horizontal drop by the vertical drop, calculate the corresponding numerical quotient of the horizontal drop and vertical drop, extract the node elements corresponding to the quotient, and perform spatial mapping arrangement in combination with the full distribution structure. Arrange the multidimensional data matrix according to the numerical row and column index priority rule, convert the internal mapping parameter node format, and generate the directional skewness ratio.

5. The infrared light intensity detection method according to claim 4, characterized in that, The specific steps for S3 are as follows: S301: Based on the directional skewness ratio, determine the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board. If the voltage time-varying rate is greater than the rated upper limit threshold inside the field programmable gate array board, send a trigger level signal, import the trigger level signal into the digital signal processing channel, perform signal frequency domain conversion and rearrangement, aggregate the output node state parameters in the channel, extract the channel link mapping parameters, and generate the over-limit trigger state quantity. S302: For the over-limit trigger state quantity, collect the value of the instantaneous output voltage and the value of the trigger time length, divide the value of the instantaneous output voltage by the value of the trigger time length, calculate the quotient of the instantaneous output voltage and the trigger time length, extract the underlying timing node element of the quotient, and perform spatial mapping arrangement of the timing node element according to the numerical row and column rules to obtain the transient truncation characterization quantity. S303: Based on the transient truncation characterization, detect the voltage time-varying rate and the rated upper limit threshold inside the field-programmable gate array board. If the voltage time-varying rate is not greater than the rated upper limit threshold inside the field-programmable gate array board, retain the voltage time-varying rate, fuse the retained voltage time-varying rate and the transient truncation characterization, merge the corresponding node numerical indexes, arrange the node vector sequence according to the time-series increment priority, and establish the corrected rate of change.

6. The infrared light intensity detection method according to claim 5, characterized in that, Extract the discrete frequency band feature components of the trigger level signal and identify the center frequency value parameter of the discrete frequency band feature components; Following the rule of increasing center frequency numerical parameters, the positions of the discrete frequency band characteristic components are interchanged to generate a frequency domain transformation rearrangement sequence.

7. The infrared light intensity detection method according to claim 5, characterized in that, The specific steps of S4 are as follows: S401: Call the directional skewness ratio, collect the control end reference distribution width value, perform a multiplication operation between the control end reference distribution width value and the directional skewness ratio, calculate the corresponding product between the control end reference distribution width value and the directional skewness ratio, extract the corresponding bottom-level mapping parameter node of the product, perform serialization arrangement on the parameter node according to the row and column encoding rules, construct the multi-dimensional feature parameter matrix shape, convert the internal element space rearrangement format, and generate the skewness width correction amount; S402: Using the skewness width correction amount, multiply the correction variation rate and the skewness width correction amount, calculate the corresponding product of the correction variation rate and the skewness width correction amount, capture the time-domain distribution feature vector associated with the product, perform discretization and dimensionality reduction mapping on the time-domain distribution feature vector according to the priority order of the element nodes, rearrange the internal hierarchical mapping format of the vector architecture, and obtain the light intensity distribution reshaping amount.

8. The infrared light intensity detection method according to claim 7, characterized in that, Obtain the node position coordinates of the parameter node, and read the row interval step value and column interval step value contained in the row and column encoding rules; Based on the node position coordinates, row interval step size, and column interval step size, the parameter nodes are rearranged to establish a serialized parameter node set.

9. The infrared light intensity detection method according to claim 8, characterized in that, The specific steps of S5 are as follows: S501: Based on the light intensity distribution reshaping amount and the row and column index values, capture the underlying data nodes inside the light intensity distribution reshaping amount, collect the corresponding pixel row and column index values, perform matching and combination operations on the pixel row and column index values ​​and the underlying data nodes, calculate the mapping sites associated with the pixel row and column index values ​​and the underlying data nodes, extract the discrete element sequence associated with the mapping sites, arrange the discrete element sequence according to the numerical encoding priority, and establish an array mapping parameter set. S502: Call the array mapping parameter set, retrieve the two-dimensional vector space representation architecture, retrieve the bottom element nodes inside the two-dimensional vector space representation architecture, perform row and column position offsets on the bottom element nodes, adjust the occupancy distribution state of the bottom element nodes in the global coordinate system, reorganize the topological hierarchy of the bottom element nodes according to the matrix form configuration specification, convert the multidimensional data hierarchy format of the global coordinate system, and obtain the light intensity spatial distribution matrix.

10. An infrared light intensity detection system, characterized in that, The system is used to implement the infrared light intensity detection method according to any one of claims 1-9, the system comprising: The time-varying rate extraction module collects the output voltage value of the pixel integrating capacitor inside the infrared focal plane detector array at the end of the basic integration time period, calculates the quotient of the output voltage value and the corresponding time length value of the basic integration time period, and obtains the voltage time-varying rate. The skewness weighting construction module extracts the voltage time-varying rates corresponding to the off-axis angle pixels, right adjacent pixels, and lower adjacent pixels of the infrared optical lens group according to the voltage time-varying rate, calculates the horizontal drop of the right adjacent pixels, calculates the vertical drop of the lower adjacent pixels, calculates the quotient of the horizontal drop and the vertical drop, and constructs the skewness weighting. The signal transmission module determines the relationship between the voltage time-varying rate and the rated upper limit threshold inside the field programmable gate array board based on the directional skewness ratio. If the voltage time-varying rate is greater than the rated upper limit threshold, a trigger level signal is sent, and the quotient of the truncated instantaneous output voltage value and the trigger time length value is calculated. If the voltage time-varying rate is not greater than the rated upper limit threshold, the voltage time-varying rate is retained, and a corrected rate of change is established. The skew width correction module calculates the product of the control terminal reference distribution width value and the directional skew ratio to generate the skew width correction amount, and calculates the product of the correction variation rate and the skew width correction amount to generate the light intensity distribution reshaping amount. The spatial distribution reconstruction module, in conjunction with the row and column index values, performs matrix array position mapping on the light intensity distribution reshaping amount to construct a light intensity spatial distribution matrix.

Images