A method for AUV long-distance terrain contour assisted navigation

Abstract

The present invention discloses a long-distance terrain contour-assisted navigation method for AUVs, which belongs to the field of underwater navigation and positioning. The present invention uses a seabed terrain contour map as a priori nautical chart for matching and positioning, reduces the influence of the number of terrain features and resolution of the priori nautical chart on the matching results, and in the particle filtering process, realizes particle weight update according to the shortest distance between the particle and the contour line. According to the matching properties of the contour map, the terrain confidence is calculated using the density of the contour line, and the terrain confidence is taken into account in the contour-assisted navigation and positioning, thereby realizing long-distance terrain-assisted navigation based on the priori nautical chart with poor terrain features and low resolution. In the long-distance terrain-assisted navigation of the present invention, energy becomes an important issue that limits the AUV from achieving long-distance underwater positioning. For this reason, it is proposed to use a single-beam sonar to measure water depth information, effectively extending the underwater endurance of the AUV.

Description

Technical Field

[0001] The present invention belongs to the field of underwater navigation and positioning, and in particular relates to an AUV long-distance terrain contour auxiliary navigation method. Background Art

[0002] With the development of AUV underwater terrain-assisted navigation technology, terrain-assisted navigation methods have become a practical underwater navigation technology. With the gradual improvement of AUV technology, AUV terrain-assisted navigation technology is also developing rapidly. AUV long-range terrain-assisted navigation methods are one of the main development directions of underwater terrain-assisted navigation. Currently, AUVs use multi-beam sonar for underwater terrain-assisted navigation. Multi-beam sonar consumes too much energy, which limits the AUV's endurance. In addition, long-range terrain-assisted navigation often involves prior nautical charts with poor terrain features or low resolution. Therefore, AUV long-range seabed terrain-assisted navigation places high demands on the energy consumption of the long-range navigation process and the robustness of the positioning results.

[0003] For underwater long-range terrain-assisted navigation, researchers are using single-beam sonar instead of multi-beam sonar to measure seabed topography, reducing the energy consumption of terrain-assisted navigation systems and improving the long-range underwater endurance of AUVs. However, the limited terrain information obtained by single-beam sonar measurements reduces the robustness of positioning results. Numerous papers have proposed using single-beam sonar for underwater terrain-assisted navigation of AUVs. However, these methods rely on raster-based prior nautical charts and fail to factor in the imperfections of prior maps used for long-range terrain-assisted navigation into their matching algorithms. During long-range terrain-assisted navigation, AUVs may pass through areas with poor terrain features or low-resolution prior maps, resulting in a loss of robustness in the results obtained from long-range terrain-assisted navigation.

[0004] Purpose of the Invention

[0005] The purpose of the present invention is to overcome the problem of defects in prior nautical charts when an AUV performs long-distance terrain assisted navigation and to propose an AUV long-distance terrain contour assisted navigation method.

[0006] Technical Solution

[0007] The object of the present invention is achieved by comprising the steps of:

[0008] An AUV long-distance terrain contour assisted navigation method comprises the following steps:

[0009] Step 1: Process the known prior chart data and convert it into an isobath map. Divide the isobath map into regional grids according to the pre-set grid size to obtain a total of M isobath submaps.

[0010] Step 2: Calculate the number of isobaths C in each isobath submap area n Since the number of isobaths is related to the robustness of the terrain matching results, the number of isobaths C n Obtain the terrain confidence b of each sub-map area, and establish a sub-map confidence model based on the terrain confidence;

[0011] Step 3: Start the single-beam sonar to collect the water depth data at the location of the AUV and record the horizontal coordinate position (x * ,y * ), and the water depth measurement data h corresponding to the coordinate position * ;

[0012] Step 4: According to the horizontal position of the water depth data, the terrain confidence b at this position is obtained through the sub-map confidence model. * ;

[0013] Step 5: Water depth data h obtained from single-beam sonar measurement * , find the isobath data corresponding to the water depth data in the isobath map, and in order to improve the calculation speed, the isobath data is discretized into isobath points, and the coordinate information of the isobath points (x c ,y c );

[0014] Step 6: Use the particle filter algorithm to fuse the measured water depth data, depth contour data and position data;

[0015] Step 7: Initialize particles according to AUV motion state information;

[0016] Step 8: Calculate the position of each particle (x p ,y p ) and the corresponding isobath point (x c ,y c ) is used as the particle importance weight update standard, and the terrain confidence b at this position ... * Taking into account the weight update, the particle importance weight update is realized;

[0017] Step 9: Calculate the effective number of particles N for particle filtering eff Determine whether to perform resampling;

[0018] Step 10: Output the AUV position information estimation result (x match ,y match ) and feeds the position estimation result back to the main control computer to complete terrain-assisted positioning.

[0019] Furthermore, the calculation formula for the shortest distance d in step eight is:

[0020]

[0021] The particle weight update equation is:

[0022]

[0023] Where λ t is the particle weight at time t, (x p ,y p ) t+1 is the particle position at time t+1, b * is the topographic confidence, d is the shortest distance between the particle and the isobath point, and p(·) is the posterior probability density function of the measurement information.

[0024] Furthermore, the calculation formula for the effective particle number in step nine is:

[0025]

[0026] Furthermore, the calculation formula for the AUV position information in step 10 is:

[0027]

[0028] Technical Effects

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] This method uses a bathymetric contour map of the seafloor as a prior chart for matching and positioning, reducing the impact of the number and resolution of the prior chart's terrain features on the matching results. During the particle filtering process, particle weights are updated based on the shortest distance between the particle and the bathymetric contour. Based on the bathymetric map's matching properties, the density of the bathymetric contours is used to calculate the terrain confidence level. This confidence level is then incorporated into bathymetric-assisted navigation and positioning, enabling long-distance terrain-assisted navigation based on a prior chart with limited terrain features and low resolution.

[0031] The present invention fully considers the problems existing in long-distance terrain-assisted navigation of AUVs and proposes corresponding solutions, which can be well applied to long-distance terrain-assisted navigation and obtain robust positioning results. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a flow chart of the present invention;

[0033] Figure 2 is a flow chart of terrain confidence calculation according to the present invention;

[0034] Figure 3 It is a schematic diagram of particle weight update in the present invention. DETAILED DESCRIPTION

[0035] The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

[0036] The present invention relates to an AUV long-distance terrain contour assisted navigation method, which includes priori chart processing, terrain confidence calculation, particle distance to contour shortest distance, particle importance weight update, etc.

[0037] Combine Figure 1 To illustrate the overall implementation, the present invention first generates a bathymetric map using prior chart data. The bathymetric density of each submap is calculated through gridding, and terrain confidence is set based on the bathymetric density to obtain a terrain confidence model for subsequent weight updates. Particles are initialized based on the prior state distribution, and particle motion is updated to obtain particle position information. Single-beam sonar is used to measure the water depth at the AUV's location. This water depth data is combined with the bathymetric map to obtain bathymetric data corresponding to the water depth. Particle importance weights are updated using terrain confidence, particle location, and bathymetric location. The particle weights are then normalized. The need for resampling is determined by calculating the number of valid particles. The AUV's current position is calculated based on the particle weights and location.

[0038] Combine Figure 2 The calculation process of terrain confidence is explained. The bathymetric map is generated using prior nautical chart data. The bathymetric map is divided into several bathymetric sub-maps according to the preset grid. The bathymetric density is obtained by calculating the number of bathymetric lines in each area. The terrain confidence is determined based on the bathymetric density to complete the terrain confidence modeling.

[0039] Combine Figure 3 This paper describes how to implement terrain-aided navigation measurement updates. The water depths measured using single-beam sonar are used to generate corresponding depth contours on a depth contour map. The depth contours are then discretized into depth points. Particle position information is updated based on particle motion. The shortest distance from each particle to the corresponding depth point is calculated to update the particle importance weights. The terrain confidence model is incorporated into the weight updates to implement AUV position measurement updates.

[0040] The specific process of the present invention is as follows:

[0041] 1. Process known prior chart data, generate corresponding bathymetric maps based on the prior chart data, divide the bathymetric maps into regional grids according to the grid division standard, and obtain M sub-maps of the bathymetric maps;

[0042] 2. According to the grid division results, calculate the number of isobaths C in each isobath submap area nThe number of isobaths is related to the terrain confidence. The terrain confidence b is calculated according to the number of isobaths in the isobath submap. After completely traversing the isobath submap, the terrain confidence model of the isobath map is obtained.

[0043] 3. The AUV starts the single-beam sonar and uses it to measure the water depth data at the AUV's location. The horizontal coordinate position (x * ,y * ), and the measured water depth data h * ;

[0044] 4. Find the depth contour submap at the horizontal position of the water depth data, and obtain the depth contour topography confidence b at this position according to the confidence b corresponding to the submap. * ;

[0045] 5. Water depth data h obtained from single-beam sonar measurement * , find the isobath corresponding to the water depth value in the isobath map as C l Since the calculation amount of matching directly with isobaths is large, in order to improve the operation speed, the isobath data is discretized into isobath point data to obtain the coordinate information of isobath points (x c ,y c );

[0046] 6. In actual application, the particle filter algorithm is used to fuse the water depth, discrete point data of the isobath measured by single-beam sonar, and the particle location information to update the particle importance weight and complete the seabed terrain assisted navigation positioning;

[0047] 7. In the particle filter, particles are initialized according to the prior state information of the AUV, and the initial particle position distribution and weight setting are completed;

[0048] 8. According to the particle motion update, the position information of each particle after the motion update is (x p ,y p ), calculate the distance between the particle position and the corresponding discrete point of the isobath (x c ,y c ) and uses it as the particle importance weight update standard. The shortest distance calculation formula is:

[0049]

[0050] The calculated terrain confidence b * Taking into account the weight update, suppressing the particle weight update in the area with low confidence to achieve the measurement update of the AUV state, the weight update formula is:

[0051]

[0052] Where λ t is the particle weight at time t, (x p ,y p ) t+1 is the particle position at time t+1, b * is the topographic confidence, d is the shortest distance between the particle and the isobath point, and p(·) is the posterior probability density function of the measurement information.

[0053] 9. Calculate the effective number of particles in the particle filter to determine whether to resample. The formula for calculating the effective number of particles is:

[0054]

[0055] Set the particle resampling threshold to N th If the number of effective particles is greater than the set threshold, no resampling is performed, otherwise resampling is performed, and the weight of each particle is resampled by the bootstrap method, and the new particle weight is set as

[0056] 10. Output the AUV position information estimation result based on the particle weight and position status information in the particle filter The position estimation results are fed back to the main control computer to complete terrain-assisted positioning.

[0057] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for AUV long-distance terrain contour assisted navigation, characterized by: The following steps are involved: Step 1: Process the known prior chart data and convert it into an isobath map. Divide the isobath map into regional grids according to the pre-set grid size to obtain a total of M isobath submaps. Step 2: Calculate the number of isobaths C in each isobath submap area n Since the number of isobaths is related to the robustness of the terrain matching results, the number of isobaths C n Obtain the terrain confidence b of each sub-map area, and establish a sub-map confidence model based on the terrain confidence; Step 3: Start the single-beam sonar to collect the water depth data at the location of the AUV and record the horizontal coordinate position (x * ,y * ), and the water depth measurement data h corresponding to the coordinate position * ; Step 4: According to the horizontal position of the water depth data, the terrain confidence b at this position is obtained through the sub-map confidence model. * ; Step 5: Water depth data h obtained from single-beam sonar measurement * , find the isobath data corresponding to the water depth data in the isobath map, and in order to improve the calculation speed, the isobath data is discretized into isobath points, and the coordinate information of the isobath points (x c ,y c ); Step 6: Use the particle filter algorithm to fuse the measured water depth data, depth contour data and position data; Step 7: Initialize particles according to AUV motion state information; Step 8: Calculate the position of each particle (x p ,y p ) and the corresponding isobath point (x c ,y c ) is used as the particle importance weight update standard, and the terrain confidence b at this position ... * Taking into account the weight update, the particle importance weight update is realized; The calculation formula for the shortest distance d is: The particle weight update equation is: Where λ t is the particle weight at time t, (x p ,y p ) t+1 is the particle position at time t+1, b * is the topographic confidence, d is the shortest distance between the particle and the isobath point, and p(·) is the posterior probability density function of the measurement information; Step 9: Calculate the effective number of particles N for particle filtering eff Determine whether to perform resampling; Step 10: Output the AUV position information estimation result (x match ,y match ) and feeds the position estimation result back to the main control computer to complete terrain-assisted positioning.

2. The AUV long-distance terrain contour assisted navigation method according to claim 1, characterized in that: The calculation formula for the effective particle number in step nine is: 。 3. The AUV long-distance terrain contour assisted navigation method according to claim 1, characterized in that: The calculation formula of AUV position information in step 10 is:

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