1. An unmanned aerial vehicle surveying and mapping method based on an adaptive algorithm is characterized by comprising the following steps: obtain unmanned aerial vehicle survey and drawing data and correspond communication transmission signal B₁S(t)cos(w_ct+θ₁) Wherein B is₁Transmitting signal amplitude adjustment values for communication, S (t) mapping data, w_cIs the carrier frequency, θ₁Transmitting a signal phase value for the communication; complementing the communication transmission signal according to the air pressure, the height of the unmanned aerial vehicle and the brightness data, wherein the complementing value is B₂cos(w_ct+θ₂)，B₂To complement the amplitude empirical value, complement the amplitude empirical value B₂Air shot by unmanned aerial vehicleThe difference values of the pressure, the height of the unmanned aerial vehicle and the brightness are positively correlated with the difference values of the standard set values; combining the communication transmission signal and the complementary value, modulating the combined signal to an intermediate frequency, and transmitting the intermediate frequency to a background server; demodulating a signal received by a background server, acquiring demodulated mapping image data, preprocessing the demodulated mapping image data, matching historical mapping data information according to the characteristic information of the preprocessed mapping image data, displaying the preprocessed characteristic information and the historical mapping data information successfully matched, and otherwise, adding or replacing the preprocessed characteristic information into the historical mapping data information; the characteristic information of the mapping image data comprises video image information, contour line data information and azimuth information; the matching comprises the following steps: the obtained characteristic information of the preprocessed mapping image data comprises pixel point information, corresponding contour line information and azimuth information, a three-dimensional stereo information search window is formed, the search window traverses historical mapping data information, after the traversal of the current search window is completed, the characteristic information of the preprocessed mapping image data obtained in the next frame forms a new search window to traverse, whether the matching is successful or not is determined by the similarity degree from the pixel point at the position of the search window to the pixel point at the position corresponding to the historical mapping data, and the similarity degree is determined by the space distance F_dAnd an association distance F_sIs shown in the specification, wherein F_d(i,j)＝F_d(d_EU(i,j))，F_s(i,j)＝F_s(d_RV(g_i,g_j))，d_EU(i, j) is the spatial distance between pixel i and pixel j, d_RV(g_i,g_j) Is the associated distance of pixel i and pixel j;

wherein the content of the first and second substances,

i_xabscissa, i, representing pixel i of the surveying image data_yOrdinate, i, representing pixel i of the surveying image data_zRepresenting mapping image dataContour height, j, of pixel i_xAbscissa, j, representing historical mapping data pixel j_yOrdinate, j, representing historical mapping data pixel j_zRepresenting the contour height of a historical mapping data pixel j;

spacing F_dIs a gaussian function with values:

wherein k is_dIs a set value, σ_dIs an error value, the spatial distance function is inversely proportional to the distance of pixel i and pixel j; correlation distance F_sThe values of (A) are:

wherein k is_sIs a custom value, σ_sError criterion, r (g)_i,g_j) Is a relevance value, the higher the similarity of the pixels i and j, r (g)_i,g_j) The larger the value of (c), k is a constant, RV is the weighted calculation between pixel points i and j, RV (g)_i,g_j)＝RV(XF_i,YF_j) X is an n × p matrix composed of i pixel point sets of mapping image data, Y is an n × q matrix composed of j pixel point sets of historical mapping data, and F_iIs a matrix of p x p, F_jIs a q × q matrix.

2. The method of claim 1, wherein the acquiring of the unmanned aerial vehicle mapping data and the corresponding communication transmission signal is performed by acquiring the mapping data through an industrial camera of the unmanned aerial vehicle, a GPS, a contour sensor measuring instrument, processing the mapping data, and transmitting the processed mapping data to a receiving end through a wireless antenna.

3. The unmanned aerial vehicle surveying and mapping method based on the adaptive algorithm of claim 2, wherein the communication transmission signal is combined with the complementary value and modulated to an intermediate frequency, that is, the communication transmission signal is added to the complementary value and then multiplied by the modulation signal to be modulated to an intermediate frequency signal for transmission.

4. The unmanned aerial vehicle surveying and mapping method based on the adaptive algorithm as claimed in claim 1, wherein the demodulation of the signal received by the background server is performed by using an improved baseband quadrature complex rotation (MSD) algorithm with a bidirectional power detection and regulation circuit, weighting the signal received by the radio wave array with an empirical correlation coefficient matrix, multiplying the weighted signal by a local orthogonal carrier to obtain a Hilbert transformed baseband signal, and performing phase modulation on the signal after passing through a pre-modulation filter by using a phase locker to avoid inter-symbol interference.

5. The adaptive algorithm-based unmanned aerial vehicle mapping method according to claim 1, wherein the preprocessing includes filtering, denoising and feature extraction of the demodulated survey image data.

6. The unmanned aerial vehicle surveying and mapping method based on the adaptive algorithm of claim 1, wherein the three-dimensional stereo information search window is further calculated by a degree of association between contour data information and orientation information.

7. An unmanned aerial vehicle mapping system based on adaptive algorithm, comprising: an acquisition module for acquiring unmanned aerial vehicle mapping data and corresponding communication transmission signal B₁S(t)cos(w_ct+θ₁) Wherein B is₁Transmitting signal amplitude adjustment values for communication, S (t) mapping data, w_cIs the carrier frequency, θ₁Transmitting a signal phase value for the communication; the completion module is used for completing the communication transmission signals according to the air pressure, the height of the unmanned aerial vehicle and the brightness data, and the completion value is B₂cos(w_ct+θ₂)，B₂To complement the amplitude empirical value, complement the amplitude empirical value B₂Air pressure when shooting with unmanned aerial vehicleThe height and the brightness of the unmanned aerial vehicle are positively correlated with the difference value of the standard set value; the sending module is used for combining the communication transmission signal and the complementary value and modulating the communication transmission signal and the complementary value to an intermediate frequency; the demodulation preprocessing module is used for demodulating the signals received by the background server, acquiring the demodulated mapping image data and preprocessing the mapping image data; the matching module is used for matching historical mapping data information according to the feature information of the preprocessed mapping image data, displaying the preprocessed feature information and the successfully matched historical mapping data information, and otherwise, adding or replacing the preprocessed feature information into the historical mapping data information; the characteristic information of the mapping image data comprises video image information, contour line data information and azimuth information; the matching comprises the following steps: the obtained characteristic information of the preprocessed mapping image data comprises pixel point information, corresponding contour line information and azimuth information, a three-dimensional stereo information search window is formed, the search window traverses historical mapping data information, after the traversal of the current search window is completed, the characteristic information of the preprocessed mapping image data obtained in the next frame forms a new search window to traverse, whether the matching is successful or not is determined by the similarity degree from the pixel point at the position of the search window to the pixel point at the position corresponding to the historical mapping data, and the similarity degree is determined by the space distance F_dAnd an association distance F_sIs shown in the specification, wherein F_d(i,j)＝F_d(d_EU(i,j))，F_s(i,j)＝F_s(d_RV(g_i,g_j))，d_EU(i, j) is the spatial distance between pixel i and pixel j, d_RV(g_i,g_j) Is the associated distance of pixel i and pixel j,

wherein the content of the first and second substances,

i_xabscissa, i, representing pixel i of the surveying image data_yOrdinate, i, representing pixel i of the surveying image data_zRepresenting the contour height, j, of a pixel i of the surveying image data_xAbscissa, j, representing historical mapping data pixel j_yOrdinate, j, representing historical mapping data pixel j_zRepresenting the contour height of a historical mapping data pixel j;

spacing F_dIs a gaussian function with values:

wherein k is_dIs a set value, σ_dIs an error value, the spatial distance function is inversely proportional to the distance of pixel i and pixel j; correlation distance F_sThe values of (A) are:

wherein k is_sIs a custom value, σ_sError criterion, r (g)_i,g_j) Is a relevance value, the higher the similarity of the pixels i and j, r (g)_i,g_j) The larger the value of (c), k is a constant, RV is the weighted calculation between pixel points i and j, RV (g)_i,g_j)＝RV(XF_i,YF_j) X is an n × p matrix composed of i pixel point sets of mapping image data, Y is an n × q matrix composed of j pixel point sets of historical mapping data, and F_iIs a matrix of p x p, F_jIs a q × q matrix.

8. The adaptive algorithm-based unmanned aerial vehicle mapping system according to claim 7, wherein the communication transmission signal is combined with the complementary value and modulated to an intermediate frequency, that is, the communication transmission signal is added to the complementary value and then multiplied by the modulation signal to modulate to an intermediate frequency signal for transmission.

9. The system of claim 7, wherein the demodulation of the signal received by the background server is performed by using an improved baseband quadrature rotation (MSD) algorithm with a bidirectional power detection and control circuit, that is, weighting a radio wave array received signal with an empirical correlation coefficient matrix, and then multiplying the weighted signal by a local orthogonal carrier to obtain a Hilbert transformed baseband signal, and performing phase modulation on the signal after passing through a pre-modulation filter by using a phase locker to avoid inter-symbol interference.

10. The adaptive algorithm-based unmanned aerial vehicle mapping system of claim 7, wherein the three-dimensional stereo information search window is further calculated by associating altitude data information and orientation information.

Background

At present, along with unmanned aerial vehicle electronic technology's rapid development, the relevant technique of unmanned aerial vehicle survey and drawing develops rapidly to reach and combine together with reality survey and drawing scene in addition information such as corresponding image and video, promoted the degree of accuracy and the readability of survey and drawing greatly, be the focus that computer survey and drawing and unmanned aerial vehicle field are being paid close attention to in recent years.

In the prior art, although the unmanned aerial vehicle surveying and mapping method and system are available, the surveying and mapping accuracy is low, the data transmission rate is slow, the matching with historical data cannot be realized, and the existing large demands for regular and timely updating of surveying and mapping data are not matched; the addition of information is revealed in the only related to unmanned aerial vehicle survey and drawing among the prior art, does not have the consideration to unmanned aerial vehicle survey and drawing distortion information, and the high integration matching that realizes unmanned aerial vehicle survey and drawing and reality demand is the key that realizes that unmanned aerial vehicle survey and drawing degree of accuracy and readability etc. improve by a wide margin. How to enable surveying and mapping to be more intelligent and humanized, improve the operation efficiency and accuracy of the unmanned aerial vehicle, and enhance the readability of users becomes a new research topic, but the transmission accuracy and efficiency of the existing unmanned aerial vehicle are lower; and mainly be to the processing of current survey and drawing, do not relate to the combination with historical survey and drawing data, consequently, an enhancement that can increase survey and drawing intelligent degree shows that matching technology has become the urgent need of improving the mapping effect to improve user's experience.

Disclosure of Invention

In order to solve the technical problems, the invention provides an unmanned aerial vehicle surveying and mapping method and system based on a self-adaptive algorithm, the unmanned aerial vehicle surveying and mapping method and system based on the self-adaptive algorithm obviously improve the data accuracy and transmission efficiency of the unmanned aerial vehicle, greatly enhance the accuracy and enhance the user experience; an unmanned aerial vehicle surveying and mapping method based on an adaptive algorithm comprises the following steps: obtain unmanned aerial vehicle survey and drawing data and correspond communication transmission signal B₁S(t)cos(w_ct+θ₁) Wherein B is₁Transmitting signal amplitude adjustment values for communication, S (t) mapping data, w_cIs the carrier frequency, θ₁Transmitting a signal phase value for the communication; complementing the communication transmission signal according to the air pressure, the height of the unmanned aerial vehicle and the brightness data, wherein the complementing value is B₂ cos(w_ct+θ₂)，B₂To complement the amplitude empirical value, complement the amplitude empirical value B₂Patting with unmanned aerial vehicleThe difference values of the air pressure, the height and the brightness of the unmanned aerial vehicle during shooting and the standard set value are positively correlated; combining the communication transmission signal and the complementary value, modulating the combined signal to an intermediate frequency, and transmitting the intermediate frequency to a background server; demodulating a signal received by a background server, acquiring demodulated mapping image data, preprocessing the demodulated mapping image data, matching historical mapping data information according to the characteristic information of the preprocessed mapping image data, displaying the preprocessed characteristic information and the historical mapping data information successfully matched, and otherwise, adding or replacing the preprocessed characteristic information into the historical mapping data information; the characteristic information of the mapping image data comprises video image information, contour line data information and azimuth information; the matching comprises the following steps: the obtained characteristic information of the preprocessed mapping image data comprises pixel point information, corresponding contour line information and azimuth information, a three-dimensional stereo information search window is formed, the search window traverses historical mapping data information, after the traversal of the current search window is completed, the characteristic information of the preprocessed mapping image data obtained in the next frame forms a new search window to traverse, whether the matching is successful or not is determined by the similarity degree from the pixel point at the position of the search window to the pixel point at the position corresponding to the historical mapping data, and the similarity degree is determined by the space distance F_dAnd an association distance F_sIs shown in the specification, wherein F_d(i,j)＝F_d(d_EU(i,j))，F_s(i,j)＝F_s(d_RV(g_i,g_j))，d_EU(i, j) is the spatial distance between pixel i and pixel j, d_RV(g_i,g_j) Is the associated distance of pixel i and pixel j,

wherein the content of the first and second substances,

i_xabscissa, i, representing pixel i of the surveying image data_yOrdinate, i, representing pixel i of the surveying image data_zRepresenting pixels i of the mapped image dataHeight of height line j_xAbscissa, j, representing historical mapping data pixel j_yOrdinate, j, representing historical mapping data pixel j_zRepresenting the contour height of a historical mapping data pixel j;

spacing F_dIs a gaussian function with values:

wherein k is_dIs a set value, σ_dIs an error value, the spatial distance function is inversely proportional to the distance of pixel i and pixel j; correlation distance F_sThe values of (A) are:

wherein k is_sIs a custom value, σ_sError criterion, r (g)_i,g_j) Is a relevance value, the higher the similarity of the pixels i and j, r (g)_i,g_j) The larger the value of (c), k is a constant, RV is the weighted calculation between pixel points i and j, RV (g)_i,g_j)＝RV(XF_i,YF_j) X is an n × p matrix composed of i pixel point sets of mapping image data, Y is an n × q matrix composed of j pixel point sets of historical mapping data, and F_iIs a matrix of p x p, F_jIs a q × q matrix.

Preferably, the acquiring of the unmanned aerial vehicle surveying and mapping data and the corresponding communication transmission signal is to acquire the surveying and mapping data through an unmanned aerial vehicle industrial camera, a GPS, and a contour sensor measuring instrument, process the surveying and mapping data, and send the data to a receiving end through a wireless antenna.

Preferably, the communication transmission signal and the complementary value are combined and modulated to an intermediate frequency, that is, the communication transmission signal and the complementary value are added and then multiplied by the modulation signal to be modulated to an intermediate frequency signal for transmission.

Preferably, the demodulation of the signal received by the background server is performed by using an improved baseband quadrature complex rotation MSD algorithm with a bidirectional power detection and control circuit, that is, the signal received by the radio wave array is weighted by an empirical correlation coefficient matrix and then multiplied by a local quadrature carrier to obtain a baseband signal after hilbert conversion, and a phase locker is used to perform phase modulation on the signal after passing through the pre-modulation filter, so as to avoid inter-code interference.

Preferably, the preprocessing includes filtering and denoising the demodulated plotting image data, and feature extraction.

Preferably, the three-dimensional stereo information search window further calculates the degree of association between the contour data information and the orientation information.

The invention also includes an unmanned aerial vehicle mapping system based on the adaptive algorithm, comprising: an acquisition module for acquiring unmanned aerial vehicle mapping data and corresponding communication transmission signal B₁S(t)cos(w_ct+θ₁) Wherein B is₁Transmitting signal amplitude adjustment values for communication, S (t) mapping data, w_cIs the carrier frequency, θ₁Transmitting a signal phase value for the communication; the completion module is used for completing the communication transmission signals according to the air pressure, the height of the unmanned aerial vehicle and the brightness data, and the completion value is B₂ cos(w_ct+θ₂)，B₂To complement the amplitude empirical value, complement the amplitude empirical value B₂The air pressure, the height of the unmanned aerial vehicle and the difference value of the brightness and the standard set value are positively correlated when the unmanned aerial vehicle shoots; the sending module is used for combining the communication transmission signal and the complementary value and modulating the communication transmission signal and the complementary value to an intermediate frequency; transmitting to a background server; the demodulation preprocessing module is used for demodulating the signals received by the background server, acquiring the demodulated mapping image data and preprocessing the mapping image data; the matching module is used for matching historical mapping data information according to the feature information of the preprocessed mapping image data, displaying the preprocessed feature information and the successfully matched historical mapping data information, and otherwise, adding or replacing the preprocessed feature information into the historical mapping data information; the characteristic information of the mapping image data comprises video image information, contour line data information and azimuth information; the matching comprises the following steps: the obtained characteristic information of the preprocessed surveying and mapping image data comprises pixel point information and corresponding contour linesInformation and azimuth information form a three-dimensional information search window, the search window traverses historical mapping data information, after the traversal of the current search window is completed, the feature information of the preprocessed mapping image data acquired in the next frame forms a new search window for traversal, whether the matching is successful or not is determined by the similarity degree from the pixel point at the position of the search window to the pixel point at the corresponding position of the historical mapping data, and the similarity degree is determined by the space distance F_dAnd an association distance F_sIs shown in the specification, wherein F_d(i,j)＝F_d(d_EU(i,j))，F_s(i,j)＝F_s(d_RV(g_i,g_j))，d_EU(i, j) is the spatial distance between pixel i and pixel j, d_RV(g_i,g_j) Is the associated distance of pixel i and pixel j,

wherein the content of the first and second substances,

i_xabscissa, i, representing pixel i of the surveying image data_yOrdinate, i, representing pixel i of the surveying image data_zRepresenting the contour height, j, of a pixel i of the surveying image data_xAbscissa, j, representing historical mapping data pixel j_yOrdinate, j, representing historical mapping data pixel j_zRepresenting the contour height of a historical mapping data pixel j;

spacing F_dIs a gaussian function with values:

wherein k is_dIs a set value, σ_dIs an error value, the spatial distance function is inversely proportional to the distance of pixel i and pixel j; correlation distance F_sThe values of (A) are:

wherein k is_sIs a custom value, σ_sError criterion, r (g)_i,g_j) Is a relevance value, the higher the similarity of the pixels i and j, r (g)_i,g_j) The larger the value of (c), k is a constant, RV is the weighted calculation between pixel points i and j, RV (g)_i,g_j)＝RV(XF_i,YF_j) X is an n × p matrix composed of i pixel point sets of mapping image data, Y is an n × q matrix composed of j pixel point sets of historical mapping data, and F_iIs a matrix of p x p, F_jIs a q × q matrix.

Preferably, the communication transmission signal and the complementary value are combined and modulated to an intermediate frequency, that is, the communication transmission signal and the complementary value are added and then multiplied by the modulation signal to be modulated to an intermediate frequency signal for transmission.

Preferably, the demodulation of the signal received by the background server is performed by using an improved baseband quadrature complex rotation MSD algorithm with a bidirectional power detection and control circuit, that is, the signal received by the radio wave array is weighted by an empirical correlation coefficient matrix and then multiplied by a local quadrature carrier to obtain a baseband signal after hilbert conversion, and a phase locker is used to perform phase modulation on the signal after passing through the pre-modulation filter, so as to avoid inter-code interference.

Preferably, the three-dimensional stereo information search window further calculates the degree of association between the contour data information and the orientation information.

Compared with the prior art, the technical scheme of the invention has the following beneficial effects:

the problem that unmanned aerial vehicle surveying and mapping are not related to historical surveying and mapping data in the prior art is solved, and the surveying and mapping method can realize regular and timely updating of the historical surveying and mapping data; the defects of low signal data transmission accuracy and low transmission rate in the prior art are overcome by adding the completion value and the completion amplitude empirical value; the method is characterized in that the data accuracy is greatly improved and the comparison with historical mapping data is greatly improved through the arrangement of a matching process, an improved baseband orthogonal complex rotation (MSD) algorithm with a bidirectional power detection regulation and control circuit is adopted, a radio wave array received signal and an experience correlation coefficient matrix are weighted and then multiplied by a local orthogonal carrier wave to obtain a baseband signal after Hilbert conversion, and a phase locker is adopted to carry out phase modulation on the signal after passing through a pre-modulation filter, so that intersymbol interference is avoided. The unmanned aerial vehicle surveying and mapping method and system based on the adaptive algorithm remarkably improve the data accuracy and transmission efficiency of the unmanned aerial vehicle, greatly enhance the accuracy and enhance the user experience.

Drawings

FIG. 1 is a diagram of an adaptive algorithm based unmanned aerial vehicle mapping system of the present invention;

Detailed Description

As will be appreciated by those skilled in the art, as background art shows, the conventional mapping has low accuracy, slow data transmission rate, and is unable to match with historical data, and does not match with the existing large demand for periodic and timely update of mapping data; the addition of information is revealed in the only related to unmanned aerial vehicle survey and drawing among the prior art, does not have the consideration to unmanned aerial vehicle survey and drawing distortion information, and the high integration matching that realizes unmanned aerial vehicle survey and drawing and reality demand is the key that realizes that unmanned aerial vehicle survey and drawing degree of accuracy and readability etc. improve by a wide margin. How to make surveying and mapping more intelligent and humanized, improve the operation efficiency and accuracy thereof, and enhance the readability of users becomes a new research subject. In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.

Example 1:

fig. 1 shows a diagram of an adaptive algorithm-based unmanned aerial vehicle surveying and mapping system of the present application, and in some embodiments, an adaptive algorithm-based unmanned aerial vehicle surveying and mapping method, including the steps of: obtain unmanned aerial vehicle survey and drawing data and correspond communication transmission signal B₁S(t)cos(w_ct+θ₁) Wherein B is₁Transmitting signal amplitude adjustment values for communication, S (t) mapping data, w_cIs the carrier frequency, θ₁Transmitting a signal phase value for the communication; according to the air pressure and the height of the unmanned aerial vehicle,The brightness data completes the communication transmission signal, and the completion value is B₂ cos(w_ct+θ₂)，B₂To complement the amplitude empirical value, complement the amplitude empirical value B₂The air pressure, the height of the unmanned aerial vehicle and the difference value of the brightness and the standard set value are positively correlated when the unmanned aerial vehicle shoots; combining the communication transmission signal and the complementary value, modulating the combined signal to an intermediate frequency, and transmitting the intermediate frequency to a background server; demodulating a signal received by a background server, acquiring demodulated mapping image data, preprocessing the demodulated mapping image data, matching historical mapping data information according to the characteristic information of the preprocessed mapping image data, displaying the preprocessed characteristic information and the historical mapping data information successfully matched, and otherwise, adding or replacing the preprocessed characteristic information into the historical mapping data information; the characteristic information of the mapping image data comprises video image information, contour line data information and azimuth information; the matching comprises the following steps: the obtained characteristic information of the preprocessed mapping image data comprises pixel point information, corresponding contour line information and azimuth information, a three-dimensional stereo information search window is formed, the search window traverses historical mapping data information, after the traversal of the current search window is completed, the characteristic information of the preprocessed mapping image data obtained in the next frame forms a new search window to traverse, whether the matching is successful or not is determined by the similarity degree from the pixel point at the position of the search window to the pixel point at the position corresponding to the historical mapping data, and the similarity degree is determined by the space distance F_dAnd an association distance F_sIs shown in the specification, wherein F_d(i,j)＝F_d(d_EU(i,j))，F_s(i,j)＝F_s(d_RV(g_i,g_j))，d_EU(i, j) is the spatial distance between pixel i and pixel j, d_RV(g_i,g_j) Is the associated distance of pixel i and pixel j;

wherein the content of the first and second substances,

i_xabscissa, i, representing pixel i of the surveying image data_yOrdinate, i, representing pixel i of the surveying image data_zRepresenting the contour height, j, of a pixel i of the surveying image data_xAbscissa, j, representing historical mapping data pixel j_yOrdinate, j, representing historical mapping data pixel j_zRepresenting the contour height of a historical mapping data pixel j;

spacing F_dIs a gaussian function with values:

wherein k is_dIs a set value, σ_dIs an error value, the spatial distance function is inversely proportional to the distance of pixel i and pixel j; correlation distance F_sThe values of (A) are:

wherein k is_sIs a custom value, σ_sError criterion, r (g)_i,g_j) Is a relevance value, the higher the similarity of the pixels i and j, r (g)_i,g_j) The larger the value of (c), k is a constant, RV is the weighted calculation between pixel points i and j, RV (g)_i,g_j)＝RV(XF_i,YF_j) X is an n × p matrix composed of i pixel point sets of mapping image data, Y is an n × q matrix composed of j pixel point sets of historical mapping data, and F_iIs a matrix of p x p, F_jIs a q × q matrix.

In some embodiments, the acquiring of the unmanned aerial vehicle mapping data and the corresponding communication transmission signal is to acquire the mapping data through an industrial camera of the unmanned aerial vehicle, a GPS, a contour sensor measuring instrument, process the mapping data, and send the mapping data to a receiving end through a wireless antenna.

In some embodiments, the communication transmission signal and the complementary value are combined and modulated to the intermediate frequency, that is, the communication transmission signal and the complementary value are added and then multiplied by the modulation signal to be modulated to the intermediate frequency signal for transmission.

In some embodiments, the demodulation of the signal received by the background server is performed by using an improved baseband quadrature complex rotation MSD algorithm with a bidirectional power detection and control circuit, that is, the radio wave array received signal is weighted by an empirical correlation coefficient matrix and then multiplied by a local orthogonal carrier to obtain a baseband signal after hilbert conversion, and a phase locker is used to perform phase modulation on the signal after passing through a pre-modulation filter, so as to avoid inter-symbol interference.

In some embodiments, the preprocessing includes filtering and denoising the demodulated trace image data, and feature extraction.

In some embodiments, the three-dimensional stereo information search window is further calculated by the relevance of the contour data information and the orientation information.

Example 2:

the invention also includes an unmanned aerial vehicle mapping system based on the adaptive algorithm, comprising: an acquisition module for acquiring unmanned aerial vehicle mapping data and corresponding communication transmission signal B₁S(t)cos(w_ct+θ₁) Wherein B is₁Transmitting signal amplitude adjustment values for communication, S (t) mapping data, w_cIs the carrier frequency, θ₁Transmitting a signal phase value for the communication; the completion module is used for completing the communication transmission signals according to the air pressure, the height of the unmanned aerial vehicle and the brightness data, and the completion value is B₂ cos(w_ct+θ₂)，B₂To complement the amplitude empirical value, complement the amplitude empirical value B₂The air pressure, the height of the unmanned aerial vehicle and the difference value of the brightness and the standard set value are positively correlated when the unmanned aerial vehicle shoots; the sending module is used for combining the communication transmission signal and the complementary value and modulating the communication transmission signal and the complementary value to an intermediate frequency; transmitting to a background server; the demodulation preprocessing module is used for demodulating the signals received by the background server, acquiring the demodulated mapping image data and preprocessing the mapping image data; a matching module for matching the historical mapping data information according to the feature information of the preprocessed mapping image data, displaying the preprocessed feature information and the successfully matched historical mapping data information,otherwise, adding or replacing the historical mapping data information with the preprocessed characteristic information; the characteristic information of the mapping image data comprises video image information, contour line data information and azimuth information; the matching comprises the following steps: the obtained characteristic information of the preprocessed mapping image data comprises pixel point information, corresponding contour line information and azimuth information, a three-dimensional stereo information search window is formed, the search window traverses historical mapping data information, after the traversal of the current search window is completed, the characteristic information of the preprocessed mapping image data obtained in the next frame forms a new search window to traverse, whether the matching is successful or not is determined by the similarity degree from the pixel point at the position of the search window to the pixel point at the position corresponding to the historical mapping data, and the similarity degree is determined by the space distance F_dAnd an association distance F_sIs shown in the specification, wherein F_d(i,j)＝F_d(d_EU(i,j))，F_s(i,j)＝F_s(d_RV(g_i,g_j))，d_EU(i, j) is the spatial distance between pixel i and pixel j, d_RV(g_i,g_j) Is the associated distance of pixel i and pixel j,

wherein the content of the first and second substances,

i_xabscissa, i, representing pixel i of the surveying image data_yOrdinate, i, representing pixel i of the surveying image data_zRepresenting the contour height, j, of a pixel i of the surveying image data_xAbscissa, j, representing historical mapping data pixel j_yOrdinate, j, representing historical mapping data pixel j_zRepresenting the contour height of a historical mapping data pixel j;

spacing F_dIs a gaussian function with values:

wherein k is_dIs a set value, σ_dIs an error value, the spatial distance function is inversely proportional to the distance of pixel i and pixel j; correlation distance F_sThe values of (A) are:

wherein k is_sIs a custom value, σ_sError criterion, r (g)_i,g_j) Is a relevance value, the higher the similarity of the pixels i and j, r (g)_i,g_j) The larger the value of (c), k is a constant, RV is the weighted calculation between pixel points i and j, RV (g)_i,g_j)＝RV(XF_i,YF_j) X is an n × p matrix composed of i pixel point sets of mapping image data, Y is an n × q matrix composed of j pixel point sets of historical mapping data, and F_iIs a matrix of p x p, F_jIs a q × q matrix.

In some embodiments, the communication transmission signal and the complementary value are combined and modulated to the intermediate frequency, that is, the communication transmission signal and the complementary value are added and then multiplied by the modulation signal to be modulated to the intermediate frequency signal for transmission.

In some embodiments, the demodulation of the signal received by the background server is performed by using an improved baseband quadrature complex rotation MSD algorithm with a bidirectional power detection and control circuit, that is, the radio wave array received signal is weighted by an empirical correlation coefficient matrix and then multiplied by a local orthogonal carrier to obtain a baseband signal after hilbert conversion, and a phase locker is used to perform phase modulation on the signal after passing through a pre-modulation filter, so as to avoid inter-symbol interference.

In some embodiments, the three-dimensional stereo information search window is further calculated by the relevance of the contour data information and the orientation information.

According to the unmanned aerial vehicle surveying and mapping method and system based on the adaptive algorithm, the problem that unmanned aerial vehicle surveying and mapping in the traditional technology is not related to historical surveying and mapping data is solved, and the surveying and mapping method can realize regular and timely updating of the historical surveying and mapping data; the defects of low signal data transmission accuracy and low transmission rate in the prior art are overcome by adding the completion value and the completion amplitude empirical value; the method is characterized in that the data accuracy is greatly improved and the comparison with historical mapping data is greatly improved through the arrangement of a matching process, an improved baseband orthogonal complex rotation (MSD) algorithm with a bidirectional power detection regulation and control circuit is adopted, a radio wave array received signal and an experience correlation coefficient matrix are weighted and then multiplied by a local orthogonal carrier wave to obtain a baseband signal after Hilbert conversion, and a phase locker is adopted to carry out phase modulation on the signal after passing through a pre-modulation filter, so that intersymbol interference is avoided. The unmanned aerial vehicle surveying and mapping method and system based on the adaptive algorithm remarkably improve the data accuracy and transmission efficiency of the unmanned aerial vehicle, greatly enhance the accuracy and enhance the user experience.

Those skilled in the art will appreciate that embodiments of the present application may be provided as a method, system, or computer program product and thus the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.

Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.