Method for calculating and evaluating flight path tracking precision of unmanned ship

Abstract

The invention discloses an unmanned ship track tracking precision calculation and evaluation method, and relates to the technical field of water surface unmanned equipment test. The method comprises the following steps: acquiring position information and timestamp information of an unmanned ship, and performing time synchronization processing; and when the unmanned ship autonomously sails towards a preset straight line leg or a broken line leg, the shore-based processing center respectively judges whether the track points are located in an effective judgment range of the corresponding leg, calculates track offsets, and counts an arithmetic mean value or a root-mean-square value of all the track offsets to serve as a tracking precision evaluation result of the straight line track or the broken line track. The method for evaluating the track tracking precision of the unmanned surface vehicle is formed, the algorithm is scientific and feasible, the method has the advantages of high evaluation accuracy and high evaluation efficiency, and beneficial reference is provided for test verification of related technical indexes of the unmanned surface vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of test and measurement of unmanned surface equipment, and particularly relates to a method for calculating and evaluating the track tracking accuracy of an unmanned boat. Background Art

[0002] As a new type of equipment, the comprehensive evaluation of the overall scheme of an unmanned surface boat and the test and measurement of its main tactical and technical indicators are the main means to support the comprehensive evaluation of the mission capabilities and overall effectiveness of the unmanned boat. Unmanned equipment has particularities in overall design and autonomous control compared with manned equipment. However, at present, the available application results of the test and comprehensive evaluation technology for unmanned surface boats are extremely limited, and it is difficult to accurately and efficiently evaluate the track of an unmanned surface boat. Summary of the Invention

[0003] The present invention provides a method for calculating and evaluating the track tracking accuracy of an unmanned boat to solve the problem that it is difficult to accurately and efficiently evaluate the track of an unmanned surface boat in the prior art.

[0004] To solve the above technical problems, the present invention adopts the following technical solutions:

[0005] A method for calculating and evaluating the track tracking accuracy of an unmanned boat includes:

[0006] Step 1: Deploy a positioning device on the unmanned boat to be tested, and collect the position information and timestamp information of the unmanned boat in real time through the positioning device, and send them to the shore-based processing center. The shore-based processing center performs time synchronization processing on all the position information of the obtained unmanned boats according to the timestamp information;

[0007] Step 2: When the unmanned boat autonomously sails towards a preset straight navigation section, the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of the straight navigation section according to the position information after time synchronization processing, takes the trajectory points within the effective determination range as effective track points, calculates the track offset of all the effective track points from the straight navigation section, and statistically calculates the arithmetic mean or root mean square value of all the track offsets as the evaluation result of the straight track tracking accuracy;

[0008] Step 3, when the unmanned boat sails autonomously facing at least two preset broken-line voyage segments, the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of any broken-line voyage segment according to the position information after time synchronization processing. The trajectory points within the effective determination range of any broken-line voyage segment are taken as the first-class effective trajectory points, and the trajectory points not within the effective determination range of any broken-line voyage segment are taken as the second-class effective trajectory points. For the first-class effective trajectory points, calculate the minimum value of the distances between the first-class effective trajectory points and all the broken-line voyage segments to obtain the first-class track offset. For the second-class effective trajectory points, calculate the minimum value of the distances between the second-class effective trajectory points and the vertices of all the broken-line voyage segments to obtain the second-class track offset. Statistically calculate the arithmetic mean or root mean square value of the first-class track offset and the second-class track offset as the evaluation result of the broken-line track tracking accuracy.

[0009] On this basis, the present invention can also be improved as follows:

[0010] In step 2, when the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of the straight voyage segment according to the position information of the unmanned boat, it specifically includes:

[0011] The shore-based processing center determines whether both θ1 and θ2 of the trajectory point P are less than 90 degrees according to the position information of the unmanned boat. When both θ1 and θ2 are less than 90 degrees, it is determined that the trajectory point P is within the effective determination range of the straight voyage segment;

[0012] Wherein, P is the i-th trajectory point, i = 1, 2,.., m, m is the number of trajectory points, θ1 is the included angle between AP and AB, θ2 is the included angle between BP and BA, A is the starting point of the preset straight voyage segment, and B is the ending point of the preset straight voyage segment.

[0013] On this basis, the present invention can also be improved as follows:

[0014] In step 2, calculate the track offset according to the following formula:

[0015]

[0016] Wherein, D represents the track offset, S is the area of the triangle formed by ABC, a is the length of BC, b is the length of AC, c is the length of AB, C is the j-th effective track point, j = 1, 2,.., n, and n is the number of effective track points.

[0017] On this basis, the present invention can also be improved as follows:

[0018] In step 2, calculate the arithmetic mean and root mean square value according to the following formula:

[0019]

[0020]

[0021] Among them, acc1 represents the root mean square value of the arithmetic mean of all track offsets, acc2 represents the root mean square value of all track offsets, and D n represents the track offset of all valid track points from the straight line segment.

[0022] On this basis, the present invention can also be improved as follows:

[0023] In step 3, the shore-based processing center determines whether each track point of the unmanned boat is within the effective determination range of any broken-line segment according to the position information after time synchronization processing, which specifically includes:

[0024] For the kth broken-line segment, the shore-based processing center determines whether θ1 and θ2 of the track point P are both less than 90 degrees according to the position information of the unmanned boat. When θ1 and θ2 are both less than 90 degrees, it is determined that the track point P is within the effective determination range of the kth broken-line segment:

[0025] Among them, k = 1, 2,..., K, where K is the number of line segments of the broken-line segment, P is the ith track point, i = 1, 2,.., m, where m is the number of track points, θ1 is the included angle between AP and AB, θ2 is the included angle between BP and BA, A is the starting point of the preset straight line segment, and B is the ending point of the preset straight line segment.

[0026] On this basis, the present invention can also be improved as follows:

[0027] In step 3, it further includes:

[0028] When a class of valid track points is within the effective determination range of more than two broken-line segments, in combination with the historical track situation map, through manual assisted determination, a forced membership relationship between the track and the segment is established segment by segment, and it is determined which broken-line segment a class of valid track points belong to according to the forced membership relationship.

[0029] On this basis, the present invention can also be improved as follows:

[0030] Combining the historical track situation map, through manual assisted determination, establishing a forced membership relationship between the track and the segment segment by segment, and determining which broken-line segment a class of valid track points belong to according to the forced membership relationship, specifically including:

[0031] By reading the historical data in the database, generating a historical track situation map, and sequentially displaying the broken-line segments to be evaluated on the historical track situation map;

[0032] Along the navigation trajectory direction of the unmanned boat, the membership relationship matching between each leg of the broken-line leg and its affiliated track is completed in sequence to obtain the mandatory membership relationship between the track and the leg.

[0033] According to the mandatory membership relationship, determine the associated track start point and the associated track end point of the track where a class of valid track points are located, and determine the leg to which a class of valid track points belong according to the associated track start point and the associated track end point.

[0034] On this basis, the present invention can also be improved as follows:

[0035] In step 3, calculate the arithmetic mean value and the root mean square value according to the following formulas:

[0036]

[0037] Among them, acc3 represents the arithmetic mean root value of the first-class track offset and the second-class track offset, acc4 represents the root mean square value of the first-class track offset and the second-class track offset, d n1 represents all the first-class track offsets, L n2 represents all the second-class track offsets, n1 represents the number of first-class valid track points, and n2 represents the number of second-class valid track points.

[0038] The method for calculating and evaluating the track tracking accuracy of the unmanned boat provided by the present invention proposes a test data acquisition scheme for the surface unmanned boat aiming at the test verification requirements of the key technical indicators of the surface unmanned boat, establishes a mathematical model of the straight track tracking accuracy, the rapid evaluation of the non-typical track tracking accuracy, and the sectional evaluation algorithm of the non-typical track tracking accuracy, and gives a detailed evaluation calculation process, forming a method for evaluating the track tracking accuracy of the unmanned boat. The algorithm is scientific and feasible, and has the advantages of high evaluation accuracy and high evaluation efficiency, providing a useful reference for the test verification of the relevant technical indicators of the surface unmanned boat.

[0039] The advantages of the additional aspects of the present invention will be partially given in the following description, partially will become obvious from the following description, or will be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a schematic diagram of the test data acquisition of the unmanned boat provided by the embodiment of the present invention;

[0041] Figure 2 is a schematic diagram of the determination of the effective track points of the straight track tracking provided by the embodiment of the present invention;

[0042] Figure 3 is a schematic diagram of the triangular geometric relationship of Heron's formula;

[0043] Figure 4 is a schematic diagram of the determination of the effective track points of the non-typical track provided by the embodiment of the present invention;

[0044] Figure 5 Schematic diagram of the rapid calculation process for the tracking accuracy of atypical trajectories provided by the embodiments of the present invention;

[0045] Figure 6 Schematic diagram of the segmented evaluation of atypical trajectories provided by the embodiments of the present invention;

[0046] Figure 7 Schematic diagram of the segmented calculation process for the tracking accuracy of atypical trajectories provided by the embodiments of the present invention. Detailed implementation manners

[0047] The following clearly and completely describes the technical solutions in the embodiments of the present invention with reference to 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 of 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.

[0048] To support the performance verification, performance appraisal, test training, etc. of unmanned boats, it is urgent to establish the test and evaluation capabilities of unmanned boats, form standardized and systematic methods for the test and evaluation of surface unmanned boats, and carry out the assessment and verification of the overall basic performance, autonomous capabilities, etc. of unmanned boats according to the combat mission requirements of surface unmanned boats, and propose a supporting index system and comprehensive evaluation method to provide basic conditions and essential tools for the overall technology verification and test training of surface unmanned boats.

[0049] Based on this, the present invention provides a method for calculating and evaluating the tracking accuracy of the unmanned boat's trajectory. For autonomous performance technical indicators such as straight-line trajectory tracking and atypical trajectory tracking, based on the collected test data such as the position information and timestamp of the unmanned boat, a mathematical evaluation model is studied and constructed, and the corresponding algorithm program is developed. The test data is comprehensively processed and analyzed to form the calculation and evaluation capabilities of various technical indicators of the "human-in-the-loop" unmanned boat.

[0050] The following is illustrated with specific examples.

[0051] In some embodiments, a method for calculating and evaluating the tracking accuracy of the unmanned boat's trajectory is provided, including:

[0052] Step 1, deploy a positioning device on the tested unmanned boat, and collect the position information and timestamp information of the unmanned boat in real time through the positioning device, and send them to the shore-based processing center. The shore-based processing center performs time synchronization processing on all the position information of the obtained unmanned boats according to the timestamp information;

[0053] It should be noted that by deploying differential Beidou / GPS on the unmanned surface vehicle, the position and timestamp information of the unmanned vehicle are collected in real time, and the test information is remotely transmitted back through the wireless ad-hoc network communication device. The data collection scheme is as Figure 1 shown; the Beidou / GPS acquisition device needs to have communication networking capabilities, and at the same time can locally store real-time data as redundant backup. The data collection frequency is 1-20HZ, the timestamp information accuracy reaches the millisecond level, the position accuracy reaches the meter level, and the data noise ratio is not greater than 0.1%; a time synchronization server is used to synchronize the time of the position data acquisition device at each boat end and the shore-based processing device.

[0054] Step 2: When the unmanned surface vehicle autonomously sails towards a preset straight line segment, the shore-based processing center determines whether each trajectory point of the unmanned surface vehicle is within the effective determination range of the straight line segment based on the position information after time synchronization processing, and takes the trajectory points within the effective determination range as valid trajectory points. Calculate the trajectory offset of all valid trajectory points from the straight line segment, and statistically calculate the arithmetic mean or root mean square value of all trajectory offsets as the evaluation result of the straight line trajectory tracking accuracy;

[0055] It should be noted that the unmanned surface vehicle autonomously sails towards a specified straight line segment to evaluate the trajectory tracking accuracy of the unmanned surface vehicle for the straight line segment. According to the collected position and time series of the unmanned surface vehicle, and according to the evaluation rules, valid trajectory points are extracted, and the vertical distance between the position data series of the valid trajectory points and the theoretical route (section AB) is calculated. Statistically calculate the arithmetic mean / root mean square value as the evaluation calculation result of the "straight line segment trajectory tracking accuracy".

[0056] Step 3: When the unmanned surface vehicle autonomously sails towards at least two preset broken line segments, the shore-based processing center determines whether each trajectory point of the unmanned surface vehicle is within the effective determination range of any broken line segment based on the position information after time synchronization processing, and takes the trajectory points within the effective determination range of any broken line segment as the first type of valid trajectory points, and takes the trajectory points not within the effective determination range of any broken line segment as the second type of valid trajectory points; for the first type of valid trajectory points, calculate the minimum value of the distances from the first type of valid trajectory points to all broken line segments to obtain the first type of trajectory offset; for the second type of valid trajectory points, calculate the minimum value of the distances from the second type of valid trajectory points to the vertices of all broken line segments to obtain the second type of trajectory offset; statistically calculate the arithmetic mean or root mean square value of the first type of trajectory offset and the second type of trajectory offset as the evaluation result of the broken line trajectory tracking accuracy.

[0057] It should be noted that the unmanned surface vehicle sails autonomously along a number of preset broken-line segments, and the track tracking accuracy of the unmanned surface vehicle for non-typical segments is evaluated. According to the collected position and time series of the unmanned surface vehicle, and according to the judgment rules, effective track points are extracted, and the vertical or turning vertex distances between the position data series of the effective track points and the preset route (track points A_→B→C→D_→E) are calculated, and the arithmetic mean or root mean square value is statistically calculated as the evaluation calculation result of the "non-typical track tracking accuracy".

[0058] The method for calculating and evaluating the track tracking accuracy of the unmanned surface vehicle provided in this embodiment proposes a test data acquisition scheme for the unmanned surface vehicle in view of the test verification requirements of the key technical indicators of the unmanned surface vehicle, establishes a mathematical model for the straight-line track tracking accuracy, the rapid evaluation of the non-typical track tracking accuracy, and the sectional evaluation algorithm of the non-typical track tracking accuracy, and gives a detailed evaluation calculation process, forming a method for evaluating the track tracking accuracy of the unmanned surface vehicle. The algorithm is scientific and feasible, and has the advantages of high evaluation accuracy and high evaluation efficiency, providing a useful reference for the test verification of the relevant technical indicators of the unmanned surface vehicle.

[0059] The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0060] (1) Algorithm model for evaluating the straight-line track tracking accuracy

[0061] The straight-line segment track tracking accuracy is evaluated for a specific straight-line segment. It is necessary to extract the effective position track points located within the specified route AB segment from the whole-process test track points of the test boat for evaluation and calculation. The determination algorithm is used to extract the collected data position sequence [(P1, T1), (P2, T2), (P3, T3)…(Pn, Tn)] of the test boat within the AB track segment, where P is the longitude and latitude of the unmanned surface vehicle, and T is the time stamp.

[0062] ① Effective track point determination criterion

[0063] It is necessary to determine to extract the effective position sequence of the unmanned surface vehicle in the AB segment. Figure 2 is a schematic diagram for determining effective track points, where A and B are the starting points of the specified tracking segment, the curve is the track line of the unmanned surface vehicle, point P is a certain track point on the track line within the effective range, θ1 is the angle between AP and AB, and θ2 is the angle between BP and BA. When both θ1 and θ2 are less than 90 degrees, it is determined that point P is within the effective range of the AB segment, and the remaining points are determined to be invalid points and do not participate in the calculation. The vector method is used to calculate the vector angle, as shown in the following formula:

[0064]

[0065] Since the position data of points A, B, and P are all in WGS84 geodetic coordinates and cannot be directly applied to geometric formulas for calculation, before calculating the included angle, it is necessary to convert the WGS84 geodetic coordinates (longitude and latitude) to ECEF (Earth-Centered, Earth-Fixed) geocentric and geodetic plane coordinates, and convert (lon, lat, H) in the IIA (longitude, latitude, altitude) coordinate system to (X, Y, Z) in the ECEF coordinate system. The specific formulas are as follows:

[0066]

[0067] Where lon is the longitude, lat is the latitude, H is the sea surface elevation, e is the ellipsoidal eccentricity, N is the curvature radius of the reference ellipsoid, a is the semi-major axis of the ellipsoid (taking the value of 6378.140 km), and b is the semi-minor axis of the ellipsoid (taking the value of 6356.755 km).

[0068] ② Calculation of track offset

[0069] According to the effective track point determination algorithm, a series of effective track points can be screened out, and then the track offset of all effective track points to the evaluated track segment is calculated, and then the arithmetic mean or root mean square value is statistically calculated as the track tracking accuracy of this straight line segment. The track offset refers to the perpendicular distance from the effective track point P within the AB track segment to the AB track segment, and the track deviation is calculated using Heron's formula.

[0070] First, establish a function for calculating the distance between two points' longitudes and latitudes. Let the longitude and latitude coordinates of point A be (x1, y1), and the longitude and latitude coordinates of point B be (x2, y2). Let θ be the half-versine value of the central angle corresponding to any two points on the sphere. The central angle θ and the distance D between any two points can be calculated by the following formula.

[0071]

[0072] D = R·θ

[0073] Where: R is the radius of the earth, with an average value of 6371.137 km.

[0074] Solving the perpendicular distance from the actual track point to the theoretical route can be transformed into a trigonometric geometry problem, as Figure 3 shown. AB is the theoretical route, C is the actual track point of the unmanned boat, and D is the route deviation value.

[0075] The perpendicular distance from point C to AB is D (track offset). Let the lengths of BC, AC, and AB be a, b, and c respectively.

[0076] In Heron's formula, the area of the triangle Where Then the distance

[0077] ③ Straight track tracking accuracy calculation

[0078] Statistically calculate the arithmetic mean or root mean square value of the track deviation amount D sequence of the valid track points to obtain the final track tracking accuracy acc of the AB section.

[0079]

[0080] (2) Fast evaluation algorithm model for atypical track tracking accuracy

[0081] The fast evaluation algorithm for atypical tracks is expected to directly and quickly calculate the track offset between a set of measured tracks and several specified planned polyline sections with high-speed and efficient processing logic. Therefore, it is necessary to extract a type of valid track points located within the specified route sections AB and BC from the whole-process test track points of the tested boat, as Figure 4 shown, and a second type of valid track points located outside the perpendicular range at the intersection of two straight line sections at the turning point. The two types of valid track points are respectively calculated for the track offset according to the specified calculation method, and then the atypical track tracking accuracy is statistically obtained.

[0082] ① Determination of valid track points

[0083] Before the fast evaluation calculation of atypical track tracking accuracy, it is necessary to determine the valid track points. The position sequence of the collected track points is traversed sequentially through the calculation program, and the track points are connected to the vertices of each straight line section (such as points A, B, and C) in turn to form a triangle and calculate the included angle. See the "Straight track tracking accuracy evaluation algorithm" for details. Since the atypical section consists of several straight line sections, a certain track point may be determined as a type of track point belonging to multiple straight line sections. For example Figure 4 shown, the track points P1 and P3 are respectively located within the valid ranges of the AB section and the BC section, and are determined as type I valid track points. It can be seen that point P1 is not only determined as a type I valid point belonging to the AB section, but also determined as a type I valid point belonging to the BC section. Point P2 does not belong to either the AB section or the BC section, so it is determined as a type II valid track point.

[0084] ② Track offset calculation

[0085] Based on the valid track point determination rule, for an atypical route composed of multiple consecutive straight line sections, the calculation method of the valid track point offset is as follows:

[0086] I Type I valid track points

[0087] The track offset of a type-I valid track point is obtained by calculating the perpendicular distance between this point and its associated straight-line track segment. The specific algorithm is the same as that of "straight-line track tracking accuracy". Since an atypical track segment consists of several straight-line track segments, a certain track point may be determined to belong to type-I track points of multiple straight-line track segments. It is necessary to take the minimum value of the calculated perpendicular distances to obtain the final value of the track segment to which this point actually belongs, d = min[d1, d2... d n . As Figure 4 shown, point P1 is associated with both track segments AB and BC, and the perpendicular distances are d1 and dx respectively. Therefore, the perpendicular distance d1 from point P1 to track segment AB is taken as the track offset of this point.

[0088] II Type-II valid track points

[0089] During the process of traversing and calculating the track point sequence, if a certain track point is not associated with any straight-line track segment, it is determined as a type-II track point. Calculate the distances between this point and all track segment vertices (such as A, B, C) and find the minimum value to obtain the track offset of this point, L = min[L1, L2... L n .

[0090] ③ Calculation of track tracking accuracy

[0091] Statistically calculate the sequences of track deviations d and L of valid track points to obtain the arithmetic mean value or the root mean square value, and obtain the final track tracking accuracy acc of the atypical track segment.

[0092]

[0093] The flowchart of the rapid calculation of atypical track tracking accuracy is as Figure 5 shown.

[0094] (3) Atypical track tracking accuracy segmented evaluation algorithm model

[0095] The atypical track rapid evaluation algorithm can automatically complete the membership matching relationship between each track point and the track segment according to a predetermined track point matching mathematical model by inputting a series of specified longitude and latitude coordinates of atypical track segments, and then quickly obtain the track tracking accuracy. This algorithm is efficient and fast. However, when there is a "variant track" in the actual boat test, there will be a problem of mismatching the membership matching relationship of some tracks, resulting in a decrease in calculation accuracy. As Figure 6As shown in the figure, for the tracks P0 - P1 - P2 - P3 and P5 - P6 - P7, through the quick evaluation model, each track point can be automatically matched to the correct affiliated track segment. However, for the "variant track" near the track point P4, according to the quick evaluation model, the track point P4 will be simultaneously determined as a valid point of both the CD and DE track segments. According to the principle of taking the minimum value of the point - line distance (d2 < d1), the track point P4 will ultimately be determined to be affiliated with the DE track segment, which causes the "mismatch" phenomenon of the P4 point that should originally be affiliated with the CD track segment, bringing about accuracy calculation errors.

[0096] When some unmanned boats are testing non - typical track tracking, a certain degree of "variant track" will inevitably occur. To effectively resolve the evaluation error problem, a "non - typical track segment evaluation algorithm model" is proposed. This model needs to combine the historical track situation map and, through manual assistance judgment, establish a "track - track segment" forced affiliation relationship segment by segment, so as to effectively solve the mismatch problem of some variant tracks and reduce the evaluation error.

[0097] ① Generation of historical track situation map

[0098] In the first step, by reading the historical data in the database, generate the historical track situation, such as Figure 6 the blue track line;

[0099] In the second step, it is necessary to add the function of displaying specified track points and track segments in the situation map function module. By inputting the start and end passing points, the specified track segments to be evaluated are displayed on the situation map in sequence, such as Figure 6 the brown non - typical track segment (A - B - C - D - E);

[0100] ② Track - track segment forced affiliation (type - 1 valid points)

[0101] Through the generated historical track situation map, it is necessary to manually assist in establishing the "track - track segment" forced affiliation relationship. Along the direction of the unmanned boat's navigation trajectory, complete the affiliation relationship matching between each straight - line track segment and the affiliated track in sequence. First, input the start and end coordinates of a certain straight - line segment, and then manually identify the timestamps of the start and end points of the track outside the perpendicular lines (outside 90 degrees) of the start and end passing points of the straight - line segment in the situation map. Specifically, adopt the algorithm model of the "typical track tracking accuracy evaluation algorithm (straight - line segment)". The program performs valid point identification calculations for the selected track segment and this straight - line segment, traverses and calculates the selected track segment in sequence, identifies the first "type - 1 valid point" (the triangle formed by the track point and the start and end points of the track segment, with both left and right included angles less than or equal to 90°) as the starting point for matching affiliation with this track segment, identifies the last "type - 1 valid point" as the ending point for matching affiliation with this track segment, and stores the timestamps of the starting point and ending point in the background database. Thus, the matching relationship calculation between part of the track and this track segment is completed.

[0102] In the evaluation of the atypical track tracking of unmanned boats, it is necessary to process three common tracks, namely, the "outer turning track" (such as the track segments P1-P2 and P5-P6), the "inner turning track" (the track segment P2-P3-P4), and the "variant track" (the track segment P3-P4-P5). The specific processing methods are as follows:

[0103] I Outer turning track

[0104] The outer turning track is defined as the track that the unmanned boat crosses the outer edge of the turning point of the track segment when turning. Taking the AB segment as an example, select a point near P0 as the starting point on the situation map, select a point in the middle of P1-P2 as the ending point (such as point P11), and input the coordinate values of the starting and ending passing points of the AB track segment in the program's human-computer interaction interface. Call the subroutine of the "linear track tracking accuracy evaluation algorithm" to perform traversal calculations on the selected track segment. It is possible to select point P0 as the starting point of the associated track of the AB segment and point P1 as the ending point of the associated track of the AB segment, and record the starting point of the time stamp of the track segment associated with AB in the background.

[0105] II Inner turning track

[0106] The inner turning track is defined as the track that converges to the inner edge of the turning point of the track segment when the unmanned boat turns. Taking the BC segment as an example, select a point in the middle of P1-P2 as the starting point (such as point P11) on the situation map, select point P3 with the same longitude as point C as the ending point, and input the coordinate values of the starting and ending passing points of the BC track segment in the program's human-computer interaction interface. Call the subroutine of the "linear track tracking accuracy evaluation algorithm" to perform traversal calculations on the selected track segment. It is possible to select point P2 as the starting point of the associated track of the BC segment and point P3 as the ending point of the associated track of the BC segment, and record the starting point of the time stamp of the track segment associated with BC in the background.

[0107] III Variant track

[0108] The variant track is defined as a special track that, when the unmanned boat is sailing in a straight line, due to navigation control failures or insufficient stability, after a large track deviation occurs, part of the track matches other straight track segments. Taking the CD segment as an example, select point P3 with the same longitude as point C as the starting point on the situation map, select a point in the middle of P5-P6 as the ending point (such as point P22), and input the coordinate values of the starting and ending passing points of the CD track segment in the program's human-computer interaction interface. Call the subroutine of the "linear track tracking accuracy evaluation algorithm" to perform traversal calculations on the selected track segment. It is possible to select point P3 as the starting point of the associated track of the CD segment and point P5 as the ending point of the associated track of the CD segment, and record the starting point of the time stamp of the track segment associated with CD in the background. This method can forcefully determine and match the track segment near point P4 where the variation occurs to the CD segment, effectively reducing the evaluation error.

[0109] The processing logic of the DE track segment is similar to that of the AB track segment.

[0110] ③Calculation of track tracking accuracy

[0111] Statistically calculate the track deviation d of a class of valid track points and the track offset L sequence of the second-class track points, obtain the arithmetic mean value or the root mean square value, and obtain the final track tracking accuracy acc of the non-atypical track segment.

[0112]

[0113] The flowchart for calculating the non-atypical track tracking accuracy in segments is as Figure 7 shown.

[0114] Optionally, in some possible implementation manners, in step 2, the shore-based processing center determines whether each track point of the unmanned boat is within the effective determination range of the straight track segment according to the position information of the unmanned boat, specifically including:

[0115] The shore-based processing center determines whether both θ1 and θ2 of the track point P are less than 90 degrees according to the position information of the unmanned boat. When both θ1 and θ2 are less than 90 degrees, it is determined that the track point P is within the effective determination range of the straight track segment;

[0116] Wherein, P is the i-th track point, i = 1, 2,.., m, m is the number of track points, θ1 is the included angle between AP and AB, θ2 is the included angle between BP and BA, A is the starting point of the preset straight track segment, and B is the ending point of the preset straight track segment.

[0117] Optionally, in some possible implementation manners, in step 2, the track offset is calculated according to the following formula:

[0118]

[0119] Wherein, D represents the track offset, S is the area of the triangle formed by ABC, a is the length of BC, b is the length of AC, c is the length of AB, C is the j-th valid track point, j = 1, 2,.., n, and n is the number of valid track points.

[0120] Optionally, in some possible implementation manners, in step 2, the arithmetic mean value and the root mean square value are calculated according to the following formula:

[0121]

[0122] Wherein, acc1 represents the arithmetic mean root value of all track offsets, acc2 represents the root mean square value of all track offsets, and D n represents the track offset of all valid track points from the straight track segment.

[0123] Optionally, in some possible implementation manners, in step 3, the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of any broken-line flight segment according to the position information after time synchronization processing, which specifically includes:

[0124] For the kth broken-line flight segment, the shore-based processing center determines whether both θ1 and θ2 of the trajectory point P are less than 90 degrees according to the position information of the unmanned boat. When both θ1 and θ2 are less than 90 degrees, it is determined that the trajectory point P is within the effective determination range of the kth broken-line flight segment;

[0125] Where k = 1, 2,..., K, K is the number of line segments of the broken-line flight segment, P is the ith trajectory point, i = 1, 2,.., m, m is the number of trajectory points, θ1 is the included angle between AP and AB, θ2 is the included angle between BP and BA, A is the starting point of the preset straight flight segment, and B is the ending point of the preset straight flight segment.

[0126] Optionally, in some possible implementation manners, in step 3, it further includes:

[0127] When a type of valid trajectory points is within the effective determination ranges of more than two broken-line flight segments, in combination with the historical track situation map, through manual assistance determination, a forced membership relationship between the track and the flight segment is established segment by segment, and it is determined which broken-line flight segment a type of valid trajectory points belongs to according to the forced membership relationship.

[0128] Optionally, in some possible implementation manners, in combination with the historical track situation map, through manual assistance determination, a forced membership relationship between the track and the flight segment is established segment by segment, and it is determined which broken-line flight segment a type of valid trajectory points belongs to, which specifically includes:

[0129] By reading the historical data in the database, a historical track situation map is generated, and the broken-line flight segments to be evaluated are sequentially displayed on the historical track situation map;

[0130] Along the navigation trajectory direction of the unmanned boat, the membership relationship matching between each flight segment of the broken-line flight segment and the affiliated track is completed sequentially to obtain the forced membership relationship between the track and the flight segment;

[0131] According to the forced membership relationship, the associated track starting point and the associated track ending point of the track where a type of valid trajectory points is located are determined, and the flight segment to which a type of valid trajectory points belongs is determined according to the associated track starting point and the associated track ending point.

[0132] Optionally, in some possible implementation manners, in step 3, the arithmetic mean value and the root mean square value are calculated according to the following formula:

[0133]

[0134] Among them, acc3 represents the root mean square value of the arithmetic mean of the first type of track offset and the second type of track offset, acc4 represents the root mean square value of the first type of track offset and the second type of track offset, d n1 represents all the first type of track offsets, L n2 represents all the second type of track offsets, n1 represents the number of valid track points of the first type, and n2 represents the number of valid track points of the second type.

[0135] Optionally, in some possible implementation manners, it may include all or part of the above various implementation manners.

[0136] In the above description, the terminal can generally refer to devices such as mobile phones, computers, tablets, or industrial control computers.

[0137] Applications, APPs, or software, etc. refer to computer programs displayed or running on the device and used to execute specific functions.

[0138] A computer refers to a device that at least has a processor and a memory and can perform data operations. It includes not only traditional computers but also any other form of device with the above functions and structures.

[0139] A server refers to a device connected to devices such as mobile phones, computers, tablets, or industrial control computers, so as to control these devices or communicate with these devices for data. It can be a general-purpose computer that runs a specific program to implement the above functions.

[0140] It should be understood that in the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine different embodiments or examples described in this specification and partial features of different embodiments or examples.

[0141] Of course, without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and deformations according to the present invention, but these changes and deformations should all fall within the protection scope of the claims of the present invention.

Claims

1. A method for calculating and evaluating the track tracking accuracy of an unmanned boat, characterized in that, Including: Step 1: Deploy a positioning device on the subject unmanned boat. The positioning device collects the position information and timestamp information of the unmanned boat in real time and sends them to the shore-based processing center. The shore-based processing center performs time synchronization processing on the position information of all unmanned boats obtained according to the timestamp information. Step 2: When the unmanned boat sails autonomously towards a preset straight navigation section, the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of the straight navigation section according to the position information after time synchronization processing. The trajectory points within the effective determination range are used as valid track points. Calculate the track offset between all the valid track points and the straight navigation section, and statistically calculate the arithmetic mean or root mean square value of all track offsets as the straight track tracking accuracy evaluation result. Step 3: When the unmanned boat sails autonomously towards at least two preset broken-line navigation sections, the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of any broken-line navigation section according to the position information after time synchronization processing. The trajectory points within the effective determination range of any broken-line navigation section are used as the first type of valid trajectory points, and the trajectory points not within the effective determination range of any broken-line navigation section are used as the second type of valid trajectory points. For the first type of valid trajectory points, calculate the minimum value of the distances between the first type of valid track points and all broken-line navigation sections to obtain the first type of track offset. For the second type of valid trajectory points, calculate the minimum value of the distances between the second type of valid trajectory points and the vertices of all broken-line navigation sections to obtain the second type of track offset. Statistically calculate the arithmetic mean or root mean square value of the first type of track offset and the second type of track offset as the broken-line track tracking accuracy evaluation result.

2. The method for calculating and evaluating the track tracking accuracy of an unmanned boat according to claim 1, wherein, In Step 2, the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of the straight navigation section according to the position information of the unmanned boat, specifically including: The shore-based processing center determines whether both θ1 and θ2 of the trajectory point P are less than 90 degrees according to the position information of the unmanned boat. When both θ1 and θ2 are less than 90 degrees, it is determined that the trajectory point P is within the effective determination range of the straight navigation section. Wherein, P is the i-th trajectory point, i = 1, 2,..., m, m is the number of trajectory points, θ1 is the included angle between AP and AB, θ2 is the included angle between BP and BA, A is the starting point of the preset straight navigation section, and B is the ending point of the preset straight navigation section.

3. The method for calculating and evaluating the track tracking accuracy of an unmanned boat according to claim 2, characterized in that, In Step 2, calculate the track offset according to the following formula: Wherein, D represents the track offset, S is the area of the triangle formed by ABC, a is the length of BC, b is the length of AC, c is the length of AB, and C is the j-th valid track point, j = 1, 2,..., n, n is the number of valid track points.

4. The method for calculating and evaluating the track tracking accuracy of an unmanned boat according to claim 3, characterized in that, In Step 2, calculate the arithmetic mean and root mean square value according to the following formula: Among them, acc1 represents the root mean square value of the arithmetic mean of all track offsets, acc2 represents the root mean square value of all track offsets, and D n represents the track offset of all valid track points from the straight track segment.

5. The method for calculating and evaluating the track tracking accuracy of an unmanned boat according to claim 1, characterized in that In Step 3, the shore-based processing center determines whether each trajectory point of the unmanned boat is within the effective determination range of any broken-line navigation section according to the position information after time synchronization processing, specifically including: For the k-th broken-line navigation segment, the shore-based processing center determines whether both θ1 and θ2 of the trajectory point P are less than 90 degrees according to the position information of the unmanned boat. When both θ1 and θ2 are less than 90 degrees, it is determined that the trajectory point P is within the effective determination range of the k-th broken-line navigation segment; where k = 1, 2,..., K, K is the number of line segments of the broken-line navigation segment, P is the i-th trajectory point, i = 1, 2,.., m, m is the number of trajectory points, θ1 is the angle between AP and AB, θ2 is the angle between BP and BA, A is the starting point of the preset straight-line navigation segment, and B is the ending point of the preset straight-line navigation segment.

6. The method for calculating and evaluating the track tracking accuracy of an unmanned boat according to claim 5, wherein In step 3, it also includes: When a type of valid trajectory points is within the effective determination ranges of more than two broken-line navigation segments, in combination with the historical track situation map, through manual-assisted determination, a forced membership relationship between the track and the navigation segment is established segment by segment, and according to the forced membership relationship, it is determined which broken-line navigation segment a type of valid trajectory points belongs to.

7. The method for calculating and evaluating the track tracking accuracy of an unmanned boat according to claim 6, characterized in that, Combining the historical track situation map, through manual-assisted determination, establishing a forced membership relationship between the track and the navigation segment segment by segment, and determining which broken-line navigation segment a type of valid trajectory points belongs to according to the forced membership relationship, specifically including: By reading the historical data in the database, generating a historical track situation map, and sequentially displaying the broken-line navigation segments to be evaluated on the historical track situation map; Along the direction of the unmanned boat's navigation trajectory, sequentially complete the membership relationship matching between each navigation segment of the broken-line navigation segment and the affiliated track, and obtain the forced membership relationship between the track and the navigation segment; According to the forced membership relationship, determine the associated track starting point and the associated track ending point of the track where a type of valid trajectory points is located, and determine the navigation segment to which a type of valid trajectory points belongs according to the associated track starting point and the associated track ending point.

8. The method for calculating and evaluating the track tracking accuracy of an unmanned boat according to claim 7, wherein In step 3, according to the following formulas, the arithmetic mean value and the root mean square value: Among them, acc3 represents the root mean square value of the arithmetic mean of the first type of track offset and the second type of track offset, acc4 represents the root mean square value of the first type of track offset and the second type of track offset, d n1 represents all the first type of track offsets, L n2 represents all the second type of track offsets, n1 represents the number of first type of effective track points, and n2 represents the number of second type of effective track points.

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