A radar terrain contour matching and positioning method

Abstract

The present invention provides a radar terrain contour matching and positioning method. First, the imaging result information is processed by single elevation delay extraction, and the elevation gradient information of continuous elevation contours is extracted. Based on the elevation gradient information of the continuous elevation contours and prior information, a continuous equal-height point set search is performed to obtain the position information of the equal-height point group, and comprehensive fitting calculation is carried out. When the coordinate difference loss amount between the position information of the equal-height point group and the initial reference position information is the smallest, the corresponding position of the equal-height point group is regarded as the new initial position. Based on the new initial position, iterative judgment is carried out and the target position is output. In this embodiment, the projection points of the result point set are selected as the position information, making it applicable to the terrain contour matching work of the aircraft wide-beam radar, and can solve the problem of low operation efficiency of the aircraft positioning algorithm in the case of poor satellite signals, thereby realizing the fast and accurate autonomous positioning function when the satellite signal is cut off or the signal is poor.

Description

Technical Field

[0001] The present invention relates to the field of autonomous matching positioning of wide-beam radars for aircraft, and particularly to a radar terrain contour matching positioning method. Background Art

[0002] The reliability of matching positioning is the key to the application engineering of matching positioning technology. How to adapt to the positioning environment in the matching algorithm and the reliability of the method in extreme environments is a major problem in matching positioning technology. Based on the current situation, traditional algorithm designs are all targeted at the positioning requirements of underwater vehicles, with poor adaptability to the platform motion state and high computational complexity; most traditional matching methods adopt the traversal matching method. Although the traversal matching method has a simple algorithm, its computational efficiency is low, the computational process is too mechanized, and the positioning accuracy depends on the traversal density.

[0003] Currently, traditional aircraft positioning methods have the problem of relying on satellite signal information, and the computational efficiency of the positioning algorithm is relatively low when the satellite signal is cut off or the signal is poor. Summary of the Invention

[0004] Embodiments of the present invention provide a radar terrain contour matching positioning method, aiming to provide an efficient and intelligent wide-beam radar terrain contour matching positioning method to improve the autonomous positioning function.

[0005] In a first aspect, embodiments of the present invention provide a radar terrain contour matching positioning method, and the method includes the following steps:

[0006] The radar wide beam irradiates the three-dimensional terrain to obtain the imaging result information of the delay Doppler map, and uses the Bayesian estimation method to fit the Brown model to perform single-elevation delay extraction processing on the imaging result information, and extract the elevation gradient information of the continuous elevation contour;

[0007] Taking the digital elevation map of the current flight area and the initial reference position as prior information, perform a continuous equal-height point set search based on the elevation gradient information of the continuous elevation contour and the prior information to obtain the equal-height point group position information; perform comprehensive fitting calculation on the equal-height point group position information and the initial reference position information;

[0008] When the coordinate difference loss amount between the equal-height point group position information and the initial reference position information is the smallest, regard the equal-height point group position corresponding to the smallest coordinate difference loss amount as the new initial position; based on the new initial position, perform the next round of continuous equal-height point set search and iterative judgment of comprehensive fitting calculation. When the iterative judgment reaches the iterative termination condition, output the target position.

[0009] Optionally, the expression of the Brown model is as follows:

[0010]

[0011] represents the Brown model, where represents the plane impulse response of the delay-Doppler map, represents the echo delay, which is the time elapsed from signal transmission to reception, represents the frequency of the delay-Doppler map, is obtained by integrating a specified function over a circle, and describes the scattering characteristics of the detection surface when the altimeter echo is near-vertically incident, represents the plane scattering intensity probability density function of the delay-Doppler map, represents the transmission probability of the delay-Doppler map.

[0012] Optionally, the expression is as follows:

[0013]

[0014] where represents the echo delay, represents the plane spatial position of the delay-Doppler map, represents the amplitude value of the delay-Doppler map, represents the exponential term of the delay-Doppler map, represents the function of the delay-Doppler map, represents the difference term of the delay-Doppler map.

[0015] Optionally, the expression is as shown below:

[0016]

[0017] where represents the echo delay, represents the standard deviation, , represents the mean value, represents the speed of light.

[0018] Optionally, the expression is as shown below:

[0019]

[0020] where represents the echo delay, is the sampling period, is the altimeter receiving bandwidth, is the acquisition time of the delay-Doppler map, represents the frequency of the delay-Doppler map, is the sampling frequency.

[0021] Optionally, the Bayesian estimation method is used to fit the Brown model to perform single-elevation delay extraction processing on the imaging result information, and elevation gradient information of continuous elevation profiles is extracted. Specifically:

[0022] Construct a posterior probability using a Bayesian expression, and calculate the expected value of the posterior probability to obtain the echo delay estimation result; is the echo delay, which represents the time elapsed from signal transmission to reception. Based on the echo delay, the corresponding terrain height is calculated to obtain the single-elevation delay extraction processing result;

[0023] Accumulate the results of multiple single-elevation delay extraction processes to obtain the elevation values of continuous elevation profiles;

[0024] Calculate the mean value of the obtained elevation values of continuous elevation profiles to obtain the elevation mean of continuous elevation profiles, and then subtract the elevation mean from the elevation values of continuous elevation profiles to obtain the elevation gradient information of continuous elevation profiles.

[0025] Optionally, using the digital elevation map of the current flight area and the initial reference position as prior information, continuous equal-height point set search is performed based on the elevation gradient information of the continuous elevation profiles and the prior information. Specifically includes:

[0026] Pre-obtain the preselected digital elevation map of the current flight area;

[0027] Delimit the range of the preselected digital elevation map, and the delimited range is adjusted correspondingly according to the initial position and its illumination area; Using the endpoints of the illumination area as reference positions, determine a preset-sized extended area as the range of area preselection to complete the delimitation of the preselected area range of the current area;

[0028] Based on the preselected area, extract the elevation gradient information of the digital elevation map of the preselected area, that is, obtain the prior information;

[0029] Perform the continuous equal-height point set search based on the elevation gradient information of the continuous elevation profiles and the elevation gradient information of the preselected area to obtain the equal-height point group information.

[0030] Optionally, the equal-height point group position information includes the center position of the point set and the coordinate differences between each point and the center. The expression for the coordinate differences between each point and the center is:

[0031] ,

[0032] where, is the equal-height point of the delay Doppler map, is the initial reference position of the delay Doppler map, is the central coordinate of the equal height point of the delay Doppler map, is the central coordinate of the initial reference position of the delay Doppler map, is the difference between the equal height point and the central coordinate of the delay Doppler map, is the difference between the initial reference position and the central coordinate of the delay Doppler map.

[0033] Optionally, the continuous search of the set of equal height points follows the principle of minimum Euclidean distance sum, and the expression of the Euclidean distance sum is as follows:

[0034]

[0035] In the formula, is the point set each point in , is the th point in the point set after being processed by the rigid transformation , is the rigid transformation quantity, including rotation and translation transformation , is the total number of points;

[0036]

[0037] Among them, is the point set each point in , is the th point in the point set after being processed by the rigid transformation , is the translation quantity of the rigid transformation, is the rotation quantity of the rigid transformation, is the total number of points.

[0038] Optionally, the Euclidean distance expression is as follows:

[0039]

[0040] Among them, is the difference between the equal height point and the central coordinate of the delay Doppler map, is the difference between the initial reference position and the central coordinate of the delay Doppler map.

[0041] In the embodiments of the present application, the imaging result information of the delay Doppler map is obtained. In this embodiment, by combining the characteristics of the wide-beam detection radar echo and the flight operation environment of the aircraft, the Brown model is used in combination with the Bayesian estimation method for parameter fitting to extract the terrain contour features. According to the obtained continuous elevation contour information, and in combination with the prior information of the digital elevation map, a search for continuous selection of the nearest equal-height points with the single elevation point at the initial position as the center is performed to obtain the position information of the equal-height point group. Then, the position information of the equal-height point group and the initial position information are comprehensively fitted and calculated. The position of the equal-height point group corresponding to the minimum coordinate difference loss is regarded as the new initial position for iterative judgment, and iterative judgment for the next round of continuous equal-height point set search and comprehensive fitting calculation is performed. When the iterative judgment reaches the iterative termination condition, the iterative result is output.

[0042] The present application selects the projection points of the result point set as the position information, making it applicable to the terrain contour matching work of the aircraft wide-beam radar. It can solve the problem that the traditional aircraft positioning method relies on satellite signal information and has a low operation efficiency of the positioning algorithm when the satellite signal is cut off or the signal is poor, thereby realizing the fast and accurate autonomous positioning function when the satellite signal is cut off or the signal is poor. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0044] Figure 1 is a flowchart of the radar terrain contour matching and positioning method provided by the embodiments of the present invention;

[0045] Figure 2 is a specific implementation flowchart of the radar terrain contour matching and positioning method provided by the embodiments of the present invention;

[0046] Figure 3 is a model diagram of the radar terrain contour matching and positioning method provided by the embodiments of the present invention;

[0047] Figure 4 is a Brown model signal diagram provided by the embodiments of the present invention;

[0048] Figure 5 is a schematic diagram of preselection of the matching area provided by the embodiments of the present invention;

[0049] Figure 6 is a schematic diagram of matching and positioning provided by the embodiments of the present invention;

[0050] Figure 7It is the simulation terrain scene diagram provided by the embodiment of the present invention;

[0051] Figure 8 It is the delay Doppler diagram provided by the embodiment of the present invention;

[0052] Figure 9 It is the elevation extraction result diagram provided by the embodiment of the present invention;

[0053] Figure 10 It is the matching positioning result diagram provided by the embodiment of the present invention. Detailed implementation manners

[0054] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0055] As Figure 1 shown, Figure 1 It is the flowchart of a radar terrain profile matching and positioning method provided by the embodiment of the present invention. The radar terrain profile matching and positioning method includes steps 101 to 104:

[0056] Step 101: The radar wide beam irradiates the three-dimensional terrain, obtains the imaging result information of the delay Doppler diagram, performs single elevation delay extraction processing on the imaging result information by using the Bayesian estimation method to fit the Brown model, and extracts the elevation gradient information of the continuous elevation profile.

[0057] In the embodiment of the present invention, after the radar altimeter receives the backscattered signal from the ground, the processed delay Doppler diagram will be obtained after processing such as full de-chirp, intermediate frequency filtering, and FFT transformation. The delay of the delay Doppler diagram corresponds to the height between the aircraft and the ground. The above delay Doppler diagram (Delay·Doppler Map, DDM) includes the delay and Doppler information of the target.

[0058] The above Bayesian estimation method is a probability statistical method. It calculates the best parameter data by constructing models of posterior probability, likelihood function, and prior probability. The Bayesian estimation method can simply approximate the true data through the Markov chain Monte Carlo sampling method to obtain the unknown data.

[0059] The above Brown model can be understood as the echo model of the Doppler channel. The real echo signal is fitted with the model signal. After the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay amount, so as to calculate the terrain height.

[0060] The above-mentioned elevation delay extraction process can be understood as a process of extracting information about the change of terrain elevation over time or space from the imaging result.

[0061] The above-mentioned track direction can be understood as the flight path of a satellite or an aircraft. The above-mentioned two-dimensional elevation information can be understood as the terrain features in the horizontal and vertical (i.e., elevation) directions.

[0062] It should be noted that the imaging result information in the delay Doppler map of the corrected radar imaging result can be extracted, and the elevation delay extraction process is performed on the imaging result information by using the Bayesian estimation method to fit the estimation of the Brown model, so as to obtain the two-dimensional elevation information of the continuous terrain along the track direction.

[0063] Step 102: Using the digital elevation map of the current flight area and the initial reference position as prior information, perform a continuous equal-height point set search based on the elevation gradient information of the continuous elevation profile and the prior information to obtain the position information of the equal-height point group; perform a comprehensive fitting calculation on the position information of the equal-height point group and the initial reference position information.

[0064] In the embodiment of the present invention, the above-mentioned initial reference position can be understood as the initial position provided by the current aircraft.

[0065] The above-mentioned digital elevation map is a digital map containing ground elevation information, usually composed of a series of regularly or irregularly distributed points, and each point records the elevation value of the ground at that position. The digital elevation map can provide prior elevation information of the ground near the flight path, which is helpful for accurate terrain matching and positioning. Using the digital elevation map of the current flight area as prior information to guide the process of equal-height point set search can ensure the accuracy and reliability of the search result.

[0066] The above-mentioned continuous elevation profile information can be understood as the continuous change of ground elevation.

[0067] The above-mentioned equal-height points can be understood as other points with the same or similar elevation.

[0068] Using the digital elevation map of the flight area as prior information, perform a continuous selection search for the nearest equal-height points with the single elevation point of the initial position as the center on the two-dimensional elevation information of the continuous terrain along the track direction and the prior information of the digital elevation map to obtain the position information of the equal-height point group. An appropriate search range can be set during the search process, and the search range is set according to the error size. If the error is large, a larger search range needs to be set to ensure that all relevant equal-height points are included; on the contrary, if the error is small, a smaller search range can be set to improve the efficiency.

[0069] It should be noted that, based on the initial reference position, the two-dimensional elevation information of the continuous terrain along the track direction and the prior information of the digital elevation map are used to find the nearest equal-height point with the initial reference position point as the center of the circle, and it is recorded. All the continuous equal-height point data are processed by equal-height point search. After the processing is completed, the position information of the equal-height point group is obtained.

[0070] Step 103: When the coordinate difference loss amount between the position information of the equal-height point group and the initial reference position information is the smallest, the position of the equal-height point group corresponding to the smallest coordinate difference loss amount is regarded as the new initial position.

[0071] In the embodiment of the present invention, the above comprehensive fitting calculation may be a rigid transformation calculation. The rigid transformation calculation is a mathematical method for determining the position and orientation of an object in space. The rigid transformation calculation includes rotation amount operation and translation amount operation.

[0072] Furthermore, the obtained position information of the equal-height point group is combined with the initial position information to calculate the rotation amount and the translation amount. When the coordinate difference loss amount is the smallest, it is regarded as the best matching and fitting position, which means that the current position and orientation are most consistent with the position information of the equal-height point group.

[0073] Step 104: Based on the new initial position, perform the next round of iterative judgment of continuous equal-height point set search and comprehensive fitting calculation. When the iterative judgment reaches the iterative termination condition, output the target position.

[0074] Among them, the iterative termination condition means that the number of iterations reaches the preset upper limit of the number of iterations or reaches the convergence threshold. The above preset number of iterations is the upper limit of the number of iterations preset by the system, which is used to determine the iterative termination condition for the convergence effect.

[0075] In the embodiment of the present invention, the best matching and fitting position is used as the new initial position for the initial value of the next round of equal-height point search and rigid transformation calculation, which can improve the calculation accuracy and efficiency.

[0076] Furthermore, according to the new initial position, perform the next round of calculation. When the number of iterations reaches the preset upper limit of the number of iterations or the convergence threshold condition has been reached, output the iterative result, and use the aircraft projection point of the selected result point set as the target position information.

[0077] In the embodiments of the present invention, by combining the characteristics of wide-beam detection radar echoes with the flight operation environment of the aircraft, the present invention adopts the parameter fitting method of the Brown model combined with the Bayesian estimation method to extract the terrain contour features. According to the obtained continuous elevation contour information, and in cooperation with the prior information of the digital elevation map, a continuous search for the nearest equal-height points is carried out with a single elevation point at the initial position as the center of the circle, and the position information of the equal-height point group is obtained. Then, the position information of the equal-height point group and the initial position information are comprehensively fitted and calculated, and the minimum coordinate difference loss is regarded as the new initial position. When the number of iterations reaches the upper limit of the number of iterations or the convergence threshold condition is reached, the iterative result is output, and the projection point of the result point set is selected as the position information, so as to be applicable to the terrain contour matching work of the aircraft wide-beam radar. The present invention does not rely on satellite signal information and can achieve fast and accurate autonomous positioning functions when the satellite signal is cut off or the signal is poor.

[0078] In the embodiments of the present invention, the imaging result information of the delay Doppler map is obtained, and the Bayesian estimation method is used to fit the Brown model to perform elevation delay extraction processing on the imaging result information to obtain two-dimensional elevation information of the continuous terrain along the track direction; the initial reference position is obtained, and the digital elevation map of the current flight area is used as the prior information, and the two-dimensional elevation information of the continuous terrain along the track direction and the prior information of the digital elevation map are used to perform a continuous search for the nearest point equal-height point set with a single elevation point at the initial reference position as the center of the circle to obtain the position information of the equal-height point group; the position information of the equal-height point group and the initial reference position information are comprehensively fitted and calculated, and the minimum coordinate difference loss is regarded as the new initial position; based on the new initial position, when the number of iterations reaches the preset upper limit of the number of iterations, the target position is output. The present invention can solve the problem that the traditional aircraft positioning method relies on satellite signal information and the operation efficiency of the positioning algorithm is low when the satellite signal is cut off or the signal is poor, so as to achieve fast and accurate autonomous positioning functions when the satellite signal is cut off or the signal is poor.

[0079] It can be understood that in the specific embodiments of the present application, relevant data such as robot data, home equipment data, and task data are involved. When the embodiments in the present application are applied to specific products or technologies, user permission or consent needs to be obtained, and the collection, use, and processing of relevant data, as well as the training, deployment, and invocation of large language models, all need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0080] Optionally, the expression of the Brown model is as follows:

[0081]

[0082] represents the mathematical parameter echo model Brown model, simply referred to as the Brown model, where, Represents the planar impulse response of the delay Doppler map, Represents the echo delay, which is the time elapsed from signal transmission to reception, Represents the frequency of the delay Doppler map, Describes the scattering characteristics of the detection surface when the altimeter echo is near-vertical illumination by integrating a suitable function over a circle, Represents the planar scattering intensity probability density function of the delay Doppler map, Represents the transmission probability of the delay Doppler map.

[0083] In the embodiment of the present invention, the above-mentioned Brown model is the echo model of each Doppler channel. By fitting the real echo signal with the model signal, after the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay amount, and then the terrain height can be deduced. The above-mentioned Brown model can be a three-term convolution model.

[0084] The above-mentioned planar impulse response of the delay Doppler map Only depends on the time echo delay , and is obtained by integrating the illuminated area of the surface. Is obtained by integrating a suitable function over a circle, and the radius of the circle depends on time.

[0085] The above-mentioned planar impulse response of the delay Doppler map Describes the response of the system to the pulse signal at a certain time point and frequency.

[0086] The above-mentioned planar scattering intensity probability density function of the delay Doppler map Describes the probability distribution of the scattering intensity at a given time or position.

[0087] The above-mentioned transmission probability of the delay Doppler map Represents the probability that the signal can be successfully transmitted to the receiver at a certain time point and frequency.

[0088] Optionally, The expression is as follows:

[0089]

[0090] Wherein, Represents the echo delay, Represents the planar spatial position of the delay Doppler map, Represents the amplitude value of the delay Doppler map, Represents the exponential term of the delay Doppler map, Represents the function of the delay Doppler map, Represents the difference term of the delay Doppler map;

[0091] and and The related angle is defined as:

[0092]

[0093] wherein, represents the radius of the circle, represents the integral of the coordinate of, represents the integral of the coordinate of.

[0094] In the embodiment of the present invention, is obtained by integrating a suitable function over a circle, and the radius of the circle depends on time. It can be integrated into a rectangular beam by fixing the and coordinates to integrate into a rectangular beam.

[0095] Optionally, The expression of is as follows:

[0096]

[0097] wherein, represents the echo delay, represents the standard deviation, , represents the average height value.

[0098] In the embodiment of the present invention, the of the delay-Doppler map is usually approximated by a Gaussian density, and its standard deviation (STD) is related to the average height value . The above Gaussian density is used to approximately describe the probability distribution of a random variable, and the probability distribution of the random variable can be approximated by a Gaussian distribution, i.e., a normal distribution.

[0099] Optionally, The expression of is as follows:

[0100]

[0101] wherein, represents the echo delay, is the sampling period, is the altimeter receiving bandwidth, is the acquisition time of the delay-Doppler map, represents the frequency of the delay-Doppler map, is the sampling frequency.

[0102] In the embodiment of the present invention, the It is approximated by the square base number. The above square base number is the square value of a number. For example, if the base number is 2, then the square of this base number is 4.

[0103] Optionally, the Bayesian estimation method is used to fit the Brown model to perform single-elevation delay extraction processing on the imaging result information, and the elevation gradient information of the continuous elevation profile is extracted. Specifically:

[0104] Use the Bayesian expression to construct the posterior probability, and calculate the expected value of the posterior probability to obtain the echo delay Estimation result; is the echo delay, which represents the time elapsed from signal transmission to reception. According to the echo delay, the corresponding terrain height is calculated to obtain the single-elevation delay extraction processing result;

[0105] Accumulate the results of multiple single-elevation delay extraction processes to obtain the elevation values of the continuous elevation profile;

[0106] Calculate the mean value of the obtained elevation values of the continuous elevation profile to obtain the elevation mean of the continuous elevation profile, and then subtract the elevation mean from the elevation values of the continuous elevation profile to obtain the elevation gradient information of the continuous elevation profile.

[0107] The above Bayesian estimation method is a probabilistic statistical method. It calculates the best parameter data by constructing models of posterior probability, likelihood function, and prior probability. Using the Bayesian estimation method, the unknown data can be easily approximated by the Markov chain Monte Carlo sampling method to find the real data.

[0108] Among them, the Bayesian expression is as follows:

[0109]

[0110] Among them, 、 and represent the posterior probability, likelihood function, and prior probability (i.e., the prior probability of the hidden variable), respectively. is the observed data, is the echo delay, which is a hidden random variable. The likelihood function and the prior are combined to construct the posterior distribution. In the above expression, the prior probability refers to the prior probability of the hidden random variable. The likelihood function and the prior probability are combined to construct the posterior probability. Once the posterior probability is obtained, the result echo delay estimation result is obtained by calculating the expected value of the posterior probability . After conversion , the terrain height can be calculated correspondingly. Therefore, it is crucial to select an appropriate probability model in the Bayesian framework.

[0111] Sparse distributions such as Laplace are often used as priors and applied to Bayesian inference.

[0112]

[0113] Denote hyperparameters.

[0114] The likelihood function can be defined as:

[0115]

[0116] is the noise variance, and its distribution is:

[0117]

[0118] Follows an inverse gamma prior distribution, which is conjugate to the Gaussian distribution of the likelihood.

[0119] The Laplace distribution is used as a sparse prior, but it is not conjugate to the Gaussian distribution in the likelihood function. Therefore, a hierarchical method is adopted. The first layer is:

[0120]

[0121] Denote the hyperparameters in the Gaussian distribution. In the second layer, the hyperparameter is further constrained by a gamma distribution.

[0122]

[0123] It is conjugate to the Gaussian distribution in the likelihood function, and the resulting marginal prior follows a Laplace distribution that expects the assignment when . Among them, is the hyperparameter that controls sparsity.

[0124] At this point, the posterior probability density can be calculated. Its expression is as follows:

[0125]

[0126] Apply the Markov chain Monte Carlo sampling method to sample the posterior distribution, and each random variable and hyperparameter can be obtained in a closed-form solution, including the parameter echo delay.

[0127] After obtaining the elevation parameter , extract its gradient information. Calculate the mean of the obtained continuous elevation profile to get the elevation mean, and then subtract the elevation mean from the elevation values of this continuous elevation profile to obtain the elevation gradient information of the continuous elevation profile.

[0128] Optionally, a digital elevation map of the current flight area and the initial reference position are used as prior information, and a continuous contour point set search is performed based on the elevation gradient information and prior information of the continuous elevation contour, specifically including:

[0129] Get the pre-selected digital elevation map of the current flight area in advance;

[0130] The pre-selected digital elevation map is delineated, and the delineated range is adjusted accordingly according to the initial position and its irradiated area; the endpoint of the irradiated area is used as the reference position, and the extended area of the preset size is determined as the pre-selected range of the area according to factors such as the size of the irradiated range, and the pre-selected area range of the current area is delineated;

[0131] Based on the pre-selected area, the elevation gradient information of the digital elevation map of the pre-selected area is extracted to obtain the prior information;

[0132] A continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the elevation gradient information of the pre-selected area. That is, for each elevation point of the continuous elevation contour gradient, the nearest contour point search is performed in the pre-selected area to obtain the contour point group information.

[0133] This step can reduce the amount of calculation and improve positioning accuracy to a certain extent by delineating the pre-selected area.

[0134] The method of extracting the elevation gradient information of the digital elevation map in the preselected area is as follows: calculating the average elevation value of the digital elevation map of the preselected area; subtracting the calculated average elevation value of the digital elevation map of the preselected area from all elevation values of the preselected area to obtain the elevation gradient information index of the preselected area in the current area.

[0135] In the embodiment of the present invention, the digital elevation map is a digitized map containing ground elevation information, which is usually composed of a series of regularly or irregularly distributed points, each of which records the elevation value of the ground at that location. The digital elevation map can provide a priori elevation information of the ground near the flight path, which is helpful for accurate terrain matching and positioning.

[0136] Specifically, the digital elevation map matching area within the positioning error range is delineated for the digital elevation map. The delineation range is adjusted accordingly according to the initial reference position of the aircraft and its irradiation area. The pre-selected area is matched and extended in the geometric direction based on the endpoints of the irradiation area along the track to the position of the maximum theoretical error to complete the delineation of the current flight area. The endpoints of the flight irradiation area are used as the reference position, and a certain size of the extension area is determined as the pre-selected area according to factors such as the size of the irradiation range. This step can reduce the amount of calculation to a certain extent and improve positioning accuracy.

[0137] Optionally, the equal-height point group position information includes the center position of the point set and the coordinate differences between each point and the center. The expression for the coordinate differences between each point and the center is as follows:

[0138] ,

[0139] wherein, is the equal-height point of the delay Doppler map, is the initial reference position of the delay Doppler map, is the center coordinate of the equal-height point of the delay Doppler map, is the center coordinate of the initial reference position of the delay Doppler map, is the coordinate difference between the equal-height point of the delay Doppler map and the center coordinate, is the coordinate difference between the initial reference position of the delay Doppler map and the center coordinate.

[0140] Optionally, the principle followed by the equal-height point set search process is the principle of the minimum sum of Euclidean distances. The expression for the sum of Euclidean distances is as follows:

[0141]

[0142] In the formula, is each point in the point set , , is the th point in the point set after being processed by the rigid transformation , is the rigid transformation quantity, including rotation and translation transformations , is the total number of points;

[0143]

[0144] wherein, is each point in the point set , , is the th point in the point set after being processed by the rigid transformation , is the translation amount of the rigid transformation, is the rotation amount of the rigid transformation, is the total number of points.

[0145] In the embodiments of the present invention, the above Euclidean distance is the straight-line distance between two points and is used to evaluate the similarity between point sets. The smaller the distance, the higher the similarity.

[0146] The above-mentioned translation amount of the rigid transformation can be understood as the linear movement distance from one point set to another, representing the relative position change of the point set. The above-mentioned rotation amount of the rigid transformation can be understood as the rotation angle from one point set to another, representing the relative angle change of the point set.

[0147] Optionally, the Euclidean distance expression is as follows:

[0148]

[0149] Wherein, is the difference between the equal-height point of the delay Doppler map and the center coordinate, is the difference between the initial reference position of the delay Doppler map and the center coordinate.

[0150] In the embodiments of the present invention, the present invention can perform iterative operations until the number of iterations reaches the upper limit or the convergence threshold condition is reached, output the iterative result, and select the projection point of the result point set as the target position information.

[0151] As Figure 2 shown, Figure 2 is a flowchart of a radar terrain contour matching and positioning method provided by another embodiment of the present invention. Specifically, it includes steps 200 to 207:

[0152] Step 200, radar echo preprocessing.

[0153] Among them, after the radar altimeter receives the backscattered signal from the ground, after processing such as full de-chirping, intermediate frequency filtering, and FFT transformation, a processed delay Doppler map will be obtained.

[0154] Step 201, Brown model construction.

[0155] Among them, the Brown model is the echo model of each Doppler channel. The real echo signal is fitted with the model signal. After the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay amount, so as to calculate the terrain height. The Brown model can be a three-term convolution model.

[0156] Step 202, Brown model fitting, elevation parameter acquisition.

[0157] Among them, the imaging result information in the delay-Doppler map of the corrected radar imaging result is extracted, and the elevation delay of each channel is extracted by fitting the Brown model estimation using the Bayesian estimation method. The elevation is calculated based on the delay to obtain the two-dimensional elevation information of the continuous terrain along the track direction. The above-mentioned Bayesian estimation method is a probability statistical method. It calculates the best parameter data by constructing models of posterior probability, likelihood function, and prior probability. Using the Bayesian estimation method, the unknown data can be easily obtained by approximating the real data through the Markov chain Monte Carlo sampling method.

[0158] Step 203, preselection of the matching area.

[0159] Among them, using the digital elevation map of the flight area as the prior information, based on the initial position provided by the current aircraft as the initial reference position for matching, and extending a certain area range centered on the initial reference position to complete the delineation of the matching area.

[0160] Step 204, search for equal-height points.

[0161] Among them, using the digital elevation map of the flight area as the prior information, based on the obtained continuous elevation contour information, in combination with the prior information of the digital elevation map, a continuous selection and search process of the nearest equal-height points with the single elevation point of the initial position as the center is carried out. An appropriate search range needs to be set during the search process, and the search range is set according to the error size.

[0162] Step 205, calculation of rigid transformation.

[0163] Among them, the position information of the equal-height point group and the initial position information are comprehensively fitted and calculated, including rotation amount calculation and translation amount calculation. The position with the smallest coordinate difference loss is regarded as the best matching and fitting position, and this position is used as the new initial position for the next round of equal-height point search and the initial value of the rigid transformation calculation.

[0164] Step 206, determine whether to converge.

[0165] Among them, two iteration termination conditions, namely the upper limit of the iteration number and the determination of the convergence effect, are specified. When the iteration number reaches the upper limit of the iteration number or the convergence threshold condition is reached, go to step 207; otherwise, go to step 204.

[0166] Step 207, positioning result.

[0167] Among them, when the iteration number reaches the upper limit of the iteration number or the convergence threshold condition is reached, the iteration result is output, and the aircraft projection point of the result point set is selected as the aircraft position information to complete the final positioning work.

[0168] In an embodiment of the present invention, the present invention combines the characteristics of wide-beam detection radar echoes with the flight operation environment of the aircraft, adopts a parameter fitting method of the Brown model combined with the Bayesian estimation method to extract terrain contour features. According to the obtained continuous elevation contour information, combined with the prior information of the digital elevation map, a continuous selection search of the nearest equal-height points with the single elevation point of the initial position as the center is carried out to obtain the position information of the equal-height point group. Then, the position information of the equal-height point group and the initial position information are comprehensively fitted and calculated, and the minimum coordinate difference loss is regarded as the new initial position. When the number of iterations reaches the upper limit of the number of iterations or the convergence threshold condition is reached, the iterative result is output, and the projection point of the result point set is selected as the position information, so as to be applicable to the terrain contour matching work of the aircraft wide-beam radar. The present invention can realize the fast and accurate autonomous positioning function in the case where the satellite signal is cut off or the signal is poor.

[0169] As Figure 3 shown, Figure 3 is a model diagram of the radar terrain contour matching and positioning method provided by the embodiment of the present invention. Specifically, the wide beam of the radar irradiates the three-dimensional terrain. Based on the characteristics of the echo energy distribution, two-dimensional continuous terrain information is obtained across dimensions, and the gradient extraction of the elevation of the digital elevation map and the extracted elevation is completed. In the present invention, the process of fitting the echoes of each channel to the Brown echo model is a process of extracting the height by fitting the Bayesian estimation method to the Brown model.

[0170] The present invention improves the traditional ICCP positioning algorithm, enhances the adaptability of the algorithm, and based on the characteristics of the radar echo delay Doppler map data, uses an elevation contour extraction method based on the Brown model. And aiming at the problem of low operation efficiency of the traditional ICCP positioning algorithm and other vehicle positioning algorithms, the present invention adopts relevant strategies to reduce the algorithm operation amount and optimize the algorithm iteration logic.

[0171] As Figure 4 shown, Figure 4 is the Brown model signal diagram provided by the embodiment of the present invention. Specifically, after the radar altimeter receives the backscattered signal from the ground, after processes such as full de-chirp, intermediate frequency filtering, and FFT transformation, the processed delay Doppler map is obtained. The delay of the delay Doppler map corresponds to the height between the aircraft and the ground. The Brown model is the echo model of each Doppler channel. By fitting the real echo signal and the model signal, after the fitting is completed, the real echo model can be analyzed according to the model parameters to obtain the signal delay amount, so as to calculate the terrain height. The Brown model can be a three-term convolution model.

[0172] As Figure 5 shown, Figure 5It is a schematic diagram of preselecting a matching area provided by an embodiment of the present invention. Specifically, to accelerate the operation speed of iterative positioning calculation and improve the working efficiency of iterative operation, a matching area of the digital elevation map within the positioning error range can be delimited. The delimited range is adjusted correspondingly according to the original initial position of the aircraft and its irradiation area. Based on the endpoints of the along-track irradiation area, geometric direction extension is performed and extended to the position of the theoretical error maximum value. Among them, P represents the irradiation area, A represents the angle of the irradiation area relative to the DEM map, W represents the extension distance perpendicular to the irradiation area, L represents the extension distance along the irradiation area, and finally the irradiation area represented by the extended solid line is formed.

[0173] As Figure 6 shown, Figure 6 It is a schematic diagram of matching positioning provided by an embodiment of the present invention. Specifically, by using the wide-beam radar irradiation elevation extraction method, several continuous elevation values can be obtained at one time. By using multi-point one-time fast matching, there is no need to wait for the accumulation of elevation points, making the matching process have higher operation efficiency. Among them, X represents the actual position point, TP represents the matching position point, P represents the initial reference position point, and C represents the contour line of the map.

[0174] As Figures 7-9 shown, Figure 7 It is a simulated terrain scene map provided by an embodiment of the present invention, Figure 8 It is a delay Doppler map provided by an embodiment of the present invention, Figure 9 It is an elevation extraction result map provided by an embodiment of the present invention, Figure 10 It is a matching positioning result map provided by an embodiment of the present invention. Specifically, a simulation experiment can be carried out on the present invention. The simulation conditions are:

[0175]

[0176] When the initial error is 50 meters, after the elevation extraction by the Brown model and the ICCP iterative matching process, after 100 fast iterations, the positioning accuracy can reach each order of magnitude. The positioning accuracy of the present invention depends on the accuracy of the extracted terrain and the accuracy of the simulated digital elevation map. The present invention has high reliability. For the situation where individual elevation points are extracted inaccurately, the present invention has the ability to reduce the negative impact of individual bad value points, and the overall operation amount of the algorithm is small, having a broad engineering application prospect.

[0177] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above various methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0178] The above-disclosed are only the preferred embodiments of the present invention. Of course, the scope of the rights of the present invention cannot be limited thereby. Therefore, equivalent changes made according to the claims of the present invention still fall within the scope covered by the present invention.

Claims

1. A radar terrain contour matching and positioning method, characterized in that The method comprises the following steps: The wide beam of the radar is irradiated toward the three-dimensional terrain to obtain the imaging result information of the delayed Doppler map, and the Bayesian estimation method is used to fit the Brownian model to perform single elevation delay extraction processing on the imaging result information, and the elevation gradient information of the continuous elevation contour is extracted; Taking the digital elevation map of the current flight area and the initial reference position as prior information, a continuous contour point set search is performed based on the elevation gradient information of the continuous elevation profile and the prior information to obtain contour point group position information; the contour point group position information and the initial reference position information are comprehensively fitted and calculated; When the coordinate difference loss between the position information of the contour point group and the initial reference position information is minimized, the position of the contour point group corresponding to the time when the coordinate difference loss is minimized is regarded as a new initial position; Based on the new initial position, the next round of continuous isohelite point set search and iterative judgment of comprehensive fitting calculation is performed, and when the iterative judgment reaches the iteration termination condition, the target position is output.

2. The radar terrain contour matching positioning method according to claim 1, characterized in that, The Brownian model expression is as follows: , represents the Brown model, where is the plane impulse response of the delay Doppler map; is the echo delay, indicating the time elapsed from signal transmission to reception; is the frequency of the delay Doppler map; is obtained by integrating a specified function over a circle and is used to describe the scattering characteristics of the detection surface when the altimeter echo is near-vertical illumination; represents the plane scattering intensity probability density function of the delay Doppler map; represents the transmission probability of the delay Doppler map.

3. The radar terrain contour matching positioning method according to claim 2, wherein The said The expression is as follows: , where represents the echo delay, represents the speed of light, represents the planar spatial position of the delay Doppler map, represents the amplitude value of the delay Doppler map, represents the exponential term of the delay Doppler map, represents the function of the delay Doppler map, represents the difference term of the delay Doppler map, represents the coordinate integral, represents the coordinate integral.

4. The radar terrain contour matching and positioning method according to claim 2, wherein The said has the following expression: , where represents the echo delay, represents the standard deviation, , represents the average height value, represents the speed of light.

5. The radar terrain contour matching and positioning method according to claim 2, characterized in that, The said has the following expression: , where represents the echo delay, is the sampling period, is the receiving bandwidth of the altimeter, represents the frequency of the delay-Doppler map, is the sampling frequency.

6. The radar terrain contour matching and positioning method according to claim 1, wherein, The Bayesian estimation method is used to fit the Brownian model to perform single elevation delay extraction processing on the imaging result information, and to extract elevation gradient information of continuous elevation contours, specifically: Construct the posterior probability using the Bayesian expression, and calculate the expected value of the posterior probability to obtain the echo delay Estimation result; The echo delay represents the time elapsed from signal transmission to reception. Calculate the corresponding terrain height based on the echo delay to obtain the single elevation delay extraction processing result; Accumulate the results of multiple single elevation delay extraction processes to obtain continuous elevation contour elevation values; The obtained continuous elevation profile elevation values are averaged to obtain the elevation mean of the continuous elevation profile, and then the elevation mean is subtracted from the continuous elevation profile elevation value to obtain the elevation gradient information of the continuous elevation profile.

7. The radar terrain contour matching and positioning method according to claim 1, characterized in that, Taking the digital elevation map of the current flight area and the initial reference position as prior information, a continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the prior information, specifically including: Get the pre-selected digital elevation map of the current flight area in advance; The pre-selected digital elevation map is delineated, and the delineated range is adjusted accordingly according to the initial reference position and the irradiated area thereof; the endpoint of the irradiated area is used as the reference position, and an extended area of a preset size is determined as the range of the pre-selected area, thereby completing the delineation of the pre-selected area of the current area; Based on the pre-selected area, extract the elevation gradient information of the digital elevation map of the pre-selected area; The continuous contour point set search is performed based on the elevation gradient information of the continuous elevation contour and the elevation gradient information of the preselected area to obtain the contour point group information.

8. The radar terrain contour matching and positioning method according to claim 1, characterized in that The position information of the contour point group includes the center position of the point set and the coordinate difference between each point and the center, wherein the coordinate difference between each point and the center is expressed as: Among them, is the equal-height point of the delayed Doppler map, is the initial reference position of the delayed Doppler map, is the central coordinate of the equal-height point of the delayed Doppler map, is the central coordinate of the initial reference position of the delayed Doppler map, is the difference between the equal-height point and the central coordinate of the delayed Doppler map, is the difference between the initial reference position and the central coordinate of the delayed Doppler map.

9. The radar terrain contour matching and positioning method according to claim 8, wherein The continuous search of the iso-height point set follows the Euclidean distance and minimum principle. The Euclidean distance and expression are as follows: In the formula, is the point set the th point in and is the th point in the point set after being processed by the rigid transformation is the rigid transformation quantity, including rotation and translation transformations , is the total number of points; Among them, is the point set in the th point, is the point in the point set after being processed by the rotation amount of the rigid transformation, th point, is the translation amount of the rigid transformation, is the rotation amount of the rigid transformation, is the total number of points.

10. The radar terrain contour matching and positioning method according to claim 9, characterized in that, The Euclidean distance expression is as follows: Among them, is the difference between the equal height point of the delay Doppler diagram and the center coordinate, is the difference between the initial reference position of the delay Doppler diagram and the center coordinate.

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