A radar condensation point quality assessment method and system

Abstract

The present invention proposes a radar condensation point quality assessment method and system. The method includes: using the attribute value of the point track to calculate the standard deviation of the attribute, and then calculating the discrete degree assessment score of the attribute according to the standard deviation of the attribute; then performing weighted summation on different attributes according to the attribute importance to obtain the attribute discrete degree score; calculating the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth; taking the minimum number of scattered points and the maximum number of scattered points according to engineering experience, and then applying the method of the first step to calculate the point track quantity score; adding the attribute discrete degree score, azimuth distribution score and point track quantity score to obtain the point track quality total score. In the scheme proposed by the present invention, the condensation point quality score is the basis of track quality assessment, which is conducive to improving the accuracy of track quality assessment, reducing the false alarm rate, and increasing the life cycle of the target track.

Description

Technical Field

[0001] The invention belongs to the field of radar data processing, and in particular relates to a radar condensation point quality assessment method and system. Background Art

[0002] During the radar scanning process, due to the influence of internal or external environment, the point trace quality of the target echo data detected and recorded from the target extractor generally cannot reach the effect of design parameter simulation. For example, the target echo may be split in azimuth. Some target echoes contain a large amount of sidelobe information. The actual echo contains a large number of random noise, internal noise, ground clutter, positive interference and negative interference points. These interference information will have a great impact on the point trace information of the real target during condensation and track processing, causing the radar to lose continuous and stable tracking of the target.

[0003] Interference information is essentially an objective existence and cannot be completely eliminated. In order to reduce its impact on radar detection, this method innovatively proposes to evaluate the quality of radar condensation points, and use the evaluated quality information to improve the actual track lifetime and reduce the probability of false association, providing strong support for the track quality management algorithm.

[0004] Disadvantages of existing technology

[0005] In the existing track quality management algorithms, track quality assessment is generally carried out from three aspects: association quality, number of track points and number of scattered points that make up the track points. The discrete degree of scattered point attributes and azimuth distribution characteristics in the condensed points have not been evaluated and utilized. This method will evaluate the quality of condensed points from three aspects: discrete degree of point track attributes, azimuth distribution characteristics and number of point tracks, which will facilitate subsequent track processing, improve track processing efficiency and reduce the probability of false alarms. Summary of the invention

[0006] In order to solve the above technical problems, the present invention proposes a radar condensation point quality assessment method and system technical solution to solve the above technical problems.

[0007] A first aspect of the present invention discloses a radar condensation point quality assessment method, the method comprising:

[0008] Step S1, point trace attribute dispersion evaluation: use the attribute value of the point trace to calculate the standard deviation of the attribute, and then calculate the attribute dispersion evaluation score based on the attribute standard deviation; then perform weighted summation on different attributes based on the attribute importance to obtain the attribute dispersion score;

[0009] Step S2, azimuth distribution evaluation: Calculate the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth;

[0010] Step S3, point quantity score evaluation: according to engineering experience, the minimum number of scattered points and the maximum number of scattered points are taken, and then the method of step S1 is applied to obtain the attribute discrete degree score of engineering experience, that is, the point quantity score is calculated;

[0011] Step S4: Add the attribute dispersion score, orientation distribution score and point quantity score to obtain a total point quality score.

[0012] According to the method of the first aspect of the present invention, in step S1, the attributes of the point trace include: distance, azimuth, Doppler, amplitude and pitch; the discrete degree of the attribute includes: distance discrete degree, azimuth discrete degree, Doppler discrete degree, amplitude discrete degree and pitch discrete degree.

[0013] According to the method of the first aspect of the present invention, in step S1, the specific formula for calculating the discrete degree evaluation score of the attribute according to the standard deviation of the attribute includes:

[0014]

[0015] in,

[0016] G x Assess the score for the degree of dispersion of the attribute;

[0017] S x is the standard deviation of the attribute;

[0018] k1 is the coefficient.

[0019] According to the method of the first aspect of the present invention, in step S1, the specific formula for obtaining the attribute discreteness score by weighted summing different attributes according to the attribute importance includes:

[0020] G1=x1*G dis +x2*G dpl +x3*G azi +x4*G amp +x5*G tle

[0021] in,

[0022] G1 is the attribute dispersion score;

[0023] G dis Assess the score for distance dispersion;

[0024] G dpl It is the Doppler discrete range assessment score;

[0025] G azi Assess the score for the degree of orientation dispersion;

[0026] G amp Assess the score for amplitude dispersion;

[0027] G tle Assess the score for pitch dispersion;

[0028] x1, x2, x3, x4, x5 are weighting coefficients.

[0029] According to the method of the first aspect of the present invention, in step S2, the specific method for calculating the azimuth distribution score according to the table lookup front position difference of the front and rear points being less than or equal to the number of scattered point azimuth gaps and the total number of scattered points of the radar rotation azimuth includes:

[0030] According to the radar rotation speed and the time interval between radar frames, the radar rotation direction during this period is obtained;

[0031] The list of scattered points that make up the condensed points is sorted in ascending order by direction. If the number of scattered points n is greater than 2, the table lookup front position difference between the current point and the next point is calculated;

[0032] The azimuth distribution score is calculated based on the number of scattered point azimuth gaps and the total number of scattered points whose forward position difference from the front and rear points is less than or equal to the radar rotation azimuth.

[0033] According to the method of the first aspect of the present invention, in step S2, the specific formula for calculating the orientation distribution score includes:

[0034]

[0035] in,

[0036] G2 is the orientation distribution score;

[0037] m is the number of scattered point azimuth gaps whose forward position difference from the forward and backward points is less than or equal to the radar rotation azimuth;

[0038] n is the total number of scattered points;

[0039] k2 is the coefficient.

[0040] According to the method of the first aspect of the present invention, in step S2, the minimum number of scatter points is 1 and the maximum number of scatter points is 30 based on engineering experience.

[0041] A second aspect of the present invention discloses a radar condensation point quality assessment system, the system comprising:

[0042] The first processing module is configured to evaluate the discrete degree of the point trace attribute: use the attribute value of the point trace to calculate the standard deviation of the attribute, and then calculate the discrete degree evaluation score of the attribute according to the standard deviation of the attribute; and then perform weighted summation on different attributes according to the importance of the attribute to obtain the attribute discrete degree score;

[0043] The second processing module is configured to: evaluate the azimuth distribution: calculate the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth;

[0044] The third processing module is configured to: evaluate the number of traces: take the minimum number of scattered points and the maximum number of scattered points according to engineering experience, and then apply the method of step S1 to calculate the number of traces score;

[0045] The fourth processing module is configured to add the attribute discreteness score, the orientation distribution score and the point trace quantity score to obtain a total point trace quality score.

[0046] According to the system of the second aspect of the present invention, the first processing module is configured as follows: the attributes of the point traces include: distance, azimuth, Doppler, amplitude and pitch; the discrete degree of the attributes includes: distance discrete degree, azimuth discrete degree, Doppler discrete degree, amplitude discrete degree and pitch discrete degree.

[0047] According to the system of the second aspect of the present invention, the first processing module is configured to: the specific formula for calculating the discrete degree evaluation score of the attribute according to the standard deviation of the attribute includes:

[0048]

[0049] in,

[0050] G x Assess the score for the degree of dispersion of the attribute;

[0051] S x is the standard deviation of the attribute;

[0052] k1 is the coefficient.

[0053] According to the system of the second aspect of the present invention, the first processing module is configured to perform weighted summation of different attributes according to the attribute importance to obtain a specific formula for attribute discreteness score, including:

[0054] G1=x1*G dis +x2*G dpl +x3*G azi +x4*G amp +x5*G tle

[0055] in,

[0056] G1 is the attribute dispersion score;

[0057] G dis Assess the score for distance dispersion;

[0058] G dpl It is the Doppler discrete range assessment score;

[0059] G azi Assess the score for the degree of orientation dispersion;

[0060] G amp Assess the score for amplitude dispersion;

[0061] G tle Assess the score for pitch dispersion;

[0062] x1, x2, x3, x4, x5 are weighting coefficients.

[0063] According to the system of the second aspect of the present invention, the second processing module is configured to calculate the azimuth distribution score according to the table lookup front position difference of the front and rear points being less than or equal to the number of scattered point azimuth gaps and the total number of scattered points of the radar rotation azimuth:

[0064] According to the radar rotation speed and the time interval between radar frames, the radar rotation direction during this period is obtained;

[0065] The list of scattered points that make up the condensed points is sorted in ascending order by direction. If the number of scattered points n is greater than 2, the table lookup front position difference between the current point and the next point is calculated;

[0066] The azimuth distribution score is calculated based on the number of scattered point azimuth gaps and the total number of scattered points whose forward position difference from the front and rear points is less than or equal to the radar rotation azimuth.

[0067] According to the system of the second aspect of the present invention, the second processing module is configured to calculate the specific formula of the orientation distribution score including:

[0068]

[0069] in,

[0070] G2 is the orientation distribution score;

[0071] m is the number of scattered point azimuth gaps whose forward position difference from the forward and backward points is less than or equal to the radar rotation azimuth;

[0072] n is the total number of scattered points;

[0073] k2 is the coefficient.

[0074] According to the system of the second aspect of the present invention, the second processing module is configured to set the minimum scatter point number to 1 and the maximum scatter point number to 30 based on engineering experience.

[0075] The third aspect of the present invention discloses an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in any one of the radar condensation point quality assessment methods in the first aspect of the present disclosure are implemented.

[0076] The fourth aspect of the present invention discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any one of the radar condensation point quality assessment methods in the first aspect of the present disclosure are implemented.

[0077] The solution proposed by the present invention has the following beneficial effects:

[0078] (1) Reduce the data processing volume of the track processing algorithm and improve the real-time performance of the algorithm.

[0079] (2) The condensation point quality score is the basis of track quality assessment, which is conducive to improving the accuracy of track quality assessment, reducing the false alarm rate, and increasing the life cycle of the target track. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0081] Figure 1 is a flow chart of a radar condensation point quality assessment method according to an embodiment of the present invention;

[0082] Figure 2 is a flow chart of orientation distribution evaluation according to an embodiment of the present invention;

[0083] Figure 3 is a structural diagram of a radar condensation point quality assessment system according to an embodiment of the present invention;

[0084] Figure 4 The figure is a structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0085] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0086] The target points in the current circle scanned by the radar should have the following characteristics:

[0087] (1) The range, elevation, azimuth after table lookup, Doppler velocity, and amplitude are consistent, that is, the degree of dispersion of the scattered point attributes that make up the condensed point should be as small as possible (the degree of azimuth dispersion does not need to be considered for radars with non-amplitude angle measurement systems);

[0088] (2) The azimuth distribution before table lookup should be evenly distributed according to the radar turntable rotation speed and the point trace reporting data rate, that is, the azimuth distribution is displayed in the shape of eyebrows (the azimuth distribution does not need to be considered for non-mechanical scanning radars);

[0089] (3) In the target detection algorithm, the real target will have a corresponding broadening in the range dimension and Doppler dimension, that is, the same target will be composed of multiple points in one frame of data. Generally, the number of points of the target is greater than that of the clutter.

[0090] The track quality is comprehensively evaluated from the above three aspects. The higher the final score, the better the track quality. At the same time, some tracks with extremely low scores can be deleted to reduce the pressure of track processing.

[0091] A first aspect of the present invention discloses a radar condensation point quality assessment method. Figure 1 FIG. 4 is a flow chart of a radar condensation point quality assessment method according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0092] Step S1, point trace attribute dispersion evaluation: use the attribute value of the point trace to calculate the standard deviation of the attribute, and then calculate the attribute dispersion evaluation score based on the attribute standard deviation; then perform weighted summation on different attributes based on the attribute importance to obtain the attribute dispersion score;

[0093] Step S2, azimuth distribution evaluation: Calculate the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth;

[0094] Step S3, point quantity evaluation: according to engineering experience, the minimum number of scattered points and the maximum number of scattered points are taken, and then the method of step S1 is applied to calculate the point quantity score;

[0095] Step S4: Add the attribute dispersion score, orientation distribution score and point quantity score to obtain a total point quality score.

[0096] In step S1, the discrete degree of the point trace attribute is evaluated: the attribute value of the point trace is used to calculate the standard deviation of the attribute, and then the discrete degree evaluation score of the attribute is calculated based on the standard deviation of the attribute.

[0097] In some embodiments, in step S1, the attributes of the point trace include: distance, azimuth, Doppler, amplitude and pitch; the discreteness of the attributes includes: distance discreteness, azimuth discreteness, Doppler discreteness, amplitude discreteness and pitch discreteness.

[0098] The specific formula for calculating the discrete degree evaluation score of the attribute according to the standard deviation of the attribute includes:

[0099]

[0100] in,

[0101] G x Assess the score for the degree of dispersion of the attribute;

[0102] S x is the standard deviation of the attribute;

[0103] k1 is the coefficient.

[0104] The specific formula for obtaining the attribute discreteness score by weighted summing of different attributes according to the attribute importance includes:

[0105] G1=x1*G dis +x2*G dpl +x3*G azi +x4*G amp +x5*G tle

[0106] in,

[0107] G1 is the attribute dispersion score;

[0108] G dis Assess the score for distance dispersion;

[0109] G dpl It is the Doppler discrete range assessment score;

[0110] G azi Assess the score for the degree of orientation dispersion;

[0111] G amp Assess the score for amplitude dispersion;

[0112] G tle Assess the score for pitch dispersion;

[0113] x1, x2, x3, x4, x5 are weighting coefficients;

[0114] Specifically, based on a large number of experiments and tests, the study concluded that the weighting coefficients of x1, x2, x3, x4, and x5 are 0.3, 0.3, 0.2, 0.1, and 0.1, respectively.

[0115] The specific formula is as follows:

[0116] G1=0.3*G dis +0.3*G dpl +0.2*G azi +0.1*G amp +0.1*G tle

[0117] Specifically, in the discrete degree evaluation, the number of scattered points is n, i is the current point number, the current attribute of the scattered point is X[i], and the minimum attribute value is X min , attribute maximum value X max According to formula 1, the normalized value of the current attribute is X_N[i], according to formula 2, the mean value of the current attribute is X, and according to formula 3, the standard deviation of the current attribute is S x , score G x With S x Inversely proportional, multiply by coefficient k to get formula 4. According to formula 4, the current attribute score is G x , the total score of the discrete degree of point trace attributes is G1.

[0118]

[0119]

[0120]

[0121]

[0122] (a) Distance dispersion evaluation

[0123] In the current scattered point of the condensed point, the current distance is Dis[i]. According to the above calculation method, the standard deviation of the distance is S dis , the distance dispersion score is G dis .

[0124] (b) Azimuth dispersion evaluation

[0125] In the current scattered point of the condensed point, the current position after table lookup is Azi[i]. According to the above calculation method, the standard deviation of the position can be obtained as S azi, the orientation dispersion score is G azi .

[0126] (c) Doppler dispersion assessment

[0127] In the current scattered point of the condensation point, the current Doppler is Dpl[i]. According to the above calculation method, the Doppler standard deviation is S dpl , Doppler dispersion score is G dpl .

[0128] (d) Amplitude dispersion assessment

[0129] In the current scattered point of the condensed point, the current amplitude is Amp[i]. According to the above calculation method, the amplitude standard deviation can be obtained as S amp , the amplitude dispersion score is G amp .

[0130] (e) Pitch dispersion assessment

[0131] In the current scattered point of the condensed point, the current pitch is Tle[i]. According to the above calculation method, the pitch standard deviation can be obtained as S tle , the pitch dispersion score is G tle .

[0132] Formula 5 is derived from the attribute importance and measurement accuracy, and the attribute dispersion score G1 is derived based on Formula 5.

[0133] G1=0.3*G dis +0.3*G dpl +0.2*G azi +0.1*G amp +0.1*G tle (Formula 5).

[0134] In step S2, azimuth distribution evaluation: the azimuth distribution score is calculated based on the number of scattered point azimuth gaps and the total number of scattered points whose front position difference between the front and rear points is less than or equal to the radar rotation azimuth.

[0135] In some embodiments, in step S2, the specific method of calculating the azimuth distribution score according to the table lookup front position difference of the front and rear points being less than or equal to the number of scattered point azimuth gaps and the total number of scattered points of the radar rotation azimuth includes:

[0136] According to the radar rotation speed and the time interval between radar frames, the radar rotation direction during this period is obtained;

[0137] The list of scattered points that make up the condensed points is sorted in ascending order by direction. If the number of scattered points n is greater than 2, the table lookup front position difference between the current point and the next point is calculated;

[0138] The azimuth distribution score is calculated based on the number of scattered point azimuth gaps and the total number of scattered points whose forward position difference from the front and rear points is less than or equal to the radar rotation azimuth.

[0139] The specific formula for calculating the orientation distribution score includes:

[0140]

[0141] in,

[0142] G2 is the orientation distribution score;

[0143] m is the number of scattered point azimuth gaps whose forward position difference from the forward and backward points is less than or equal to the radar rotation azimuth;

[0144] n is the total number of scattered points;

[0145] k2 is the coefficient.

[0146] Specifically, Figure 2 As shown, according to the radar rotation speed R (° / s) and the time interval between radar frames T (s), the radar rotation azimuth α = R*T (°) during this period is obtained;

[0147] The scattered point list that constitutes the condensed point is sorted from small to large in terms of orientation. If the number of scattered points n is greater than 2, the position difference δ = A between the current point and the next point is calculated. i -A i,-1 ;

[0148] The number of scattered point position gaps with δ≤α is m, then Otherwise G2=0.

[0149] In step S3, point quantity evaluation: according to engineering experience, the minimum and maximum scatter points are taken, and then the method of step S1 is applied to calculate the point quantity score.

[0150] In some embodiments, in step S3, the minimum number of scatter points is 1 and the maximum number of scatter points is 30 based on engineering experience.

[0151] Specifically, the current number of scattered points is n, and the minimum number of scattered points n is taken according to engineering experience min is 1, the maximum number of scattered points is n max is 30, and from formula 1 to formula 4, we can get the dot quantity score G3.

[0152] In step S4, the attribute dispersion score, the orientation distribution score and the point quantity score are added together to obtain a total point quality score.

[0153] Specifically, the total dot quality score G=G1+G2+G3.

[0154] In summary, the solution proposed by the present invention can

[0155] (1) Reduce the data processing volume of the track processing algorithm and improve the real-time performance of the algorithm.

[0156] (2) The condensation point quality score is the basis of track quality assessment, which is conducive to improving the accuracy of track quality assessment, reducing the false alarm rate, and increasing the life cycle of the target track.

[0157] A second aspect of the present invention discloses a radar condensation point quality assessment system. Figure 3 is a structural diagram of a radar condensation point quality assessment system according to an embodiment of the present invention; Figure 3 As shown, the system 100 includes:

[0158] The first processing module 101 is configured to evaluate the discrete degree of the point trace attribute: use the attribute value of the point trace to calculate the standard deviation of the attribute, and then calculate the discrete degree evaluation score of the attribute according to the standard deviation of the attribute; and then perform weighted summation on different attributes according to the attribute importance to obtain the attribute discrete degree score;

[0159] The second processing module 102 is configured to, evaluate the azimuth distribution: calculate the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth;

[0160] The third processing module 103 is configured to: evaluate the number of traces: take the minimum number of scattered points and the maximum number of scattered points according to engineering experience, and then apply the method of step S1 to calculate the number of traces score;

[0161] The fourth processing module 104 is configured to add the attribute dispersion degree score, the orientation distribution score and the point trace quantity score to obtain a total point trace quality score.

[0162] According to the system of the second aspect of the present invention, the first processing module 101 is configured as follows: the attributes of the point traces include: distance, azimuth, Doppler, amplitude and pitch; the discrete degree of the attributes includes: distance discrete degree, azimuth discrete degree, Doppler discrete degree, amplitude discrete degree and pitch discrete degree.

[0163] According to the system of the second aspect of the present invention, the first processing module 101 is configured to: the specific formula for calculating the discrete degree evaluation score of the attribute according to the standard deviation of the attribute includes:

[0164]

[0165] in,

[0166] G x Assess the score for the degree of dispersion of the attribute;

[0167] S x is the standard deviation of the attribute;

[0168] k1 is the coefficient.

[0169] According to the system of the second aspect of the present invention, the first processing module 101 is configured to perform weighted summation of different attributes according to the attribute importance to obtain a specific formula for attribute discreteness score, including:

[0170] G1=x1*G dis +x2*G dpl +x3*G azi +x4*G amp +x5*G tle

[0171] in,

[0172] G1 is the attribute dispersion score;

[0173] G dis Assess the score for distance dispersion;

[0174] G dpl It is the Doppler discrete range assessment score;

[0175] G azi Assess the score for the degree of orientation dispersion;

[0176] G amp Assess the score for amplitude dispersion;

[0177] G tle Assess the score for pitch dispersion;

[0178] x1, x2, x3, x4, x5 are weighting coefficients.

[0179] According to the system of the second aspect of the present invention, the second processing module 102 is configured to calculate the azimuth distribution score according to the table lookup front position difference of the front and rear points being less than or equal to the number of scattered point azimuth gaps and the total number of scattered points of the radar rotation azimuth:

[0180] According to the radar rotation speed and the time interval between radar frames, the radar rotation direction during this period is obtained;

[0181] The list of scattered points that make up the condensed points is sorted in ascending order by direction. If the number of scattered points n is greater than 2, the table lookup front position difference between the current point and the next point is calculated;

[0182] The azimuth distribution score is calculated based on the number of scattered point azimuth gaps and the total number of scattered points whose forward position difference from the front and rear points is less than or equal to the radar rotation azimuth.

[0183] According to the system of the second aspect of the present invention, the second processing module 102 is configured to calculate the specific formula of the orientation distribution score including:

[0184]

[0185] in,

[0186] G2 is the orientation distribution score;

[0187] m is the number of scattered point azimuth gaps whose forward position difference from the forward and backward points is less than or equal to the radar rotation azimuth;

[0188] n is the total number of scattered points;

[0189] k2 is the coefficient.

[0190] According to the system of the second aspect of the present invention, the second processing module 102 is configured to set the minimum scatter point number to 1 and the maximum scatter point number to 30 based on engineering experience.

[0191] The third aspect of the present invention discloses an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the radar condensation point quality assessment methods disclosed in the first aspect of the present invention are implemented.

[0192] Figure 4 is a structural diagram of an electronic device according to an embodiment of the present invention, such as Figure 4 As shown, the electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, near field communication (NFC) or other technologies. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a button, a trackball or a touch pad set on the housing of the electronic device, or an external keyboard, touch pad or mouse, etc.

[0193] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a structural diagram of the part related to the technical solution of the present disclosure, and does not constitute a limitation on the electronic device to which the technical solution of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0194] The fourth aspect of the present invention discloses a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the radar condensation point quality assessment method disclosed in any one of the first aspects of the present invention are implemented.

[0195] Please note that the technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification. The above embodiments only express several implementation methods of the present application, and their descriptions are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, without departing from the concept of the present application, several variations and improvements can be made, which all belong to the scope of protection of the present application. Therefore, the scope of protection of the patent in this application shall be based on the attached claims.

Claims

1. A radar condensation point quality assessment method, characterized in that: The method comprises: Step S1, point trace attribute discreteness evaluation: use the attribute value of the point trace to calculate the standard deviation of the attribute, and then calculate the discreteness evaluation score of the attribute according to the standard deviation of the attribute; then perform weighted summation on different attributes according to the attribute importance to obtain the attribute discreteness score; the attributes of the point trace include: distance, azimuth, Doppler, amplitude and pitch; the discreteness of the attribute includes: distance discreteness, azimuth discreteness, Doppler discreteness, amplitude discreteness and pitch discreteness; Step S2, azimuth distribution evaluation: Calculate the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth; Step S3, point quantity score evaluation: according to engineering experience, the minimum number of scattered points and the maximum number of scattered points are taken, and then the method of step S1 is applied to obtain the attribute discrete degree score of engineering experience, that is, the point quantity score is calculated; Step S4, adding the attribute dispersion score, the orientation distribution score and the point quantity score to obtain a total point quality score; In step S2, the specific method for calculating the azimuth distribution score according to the table lookup front position difference of the front and rear points being less than or equal to the number of scattered point azimuth gaps and the total number of scattered points of the radar rotation azimuth includes: According to the radar rotation speed and the time interval between radar frames, the radar rotation direction during this period is obtained; The list of scattered points that make up the condensed points is sorted from small to large in terms of orientation. If the number of scattered points n is greater than 2, the table lookup front position difference between the current point and the next point is calculated; The azimuth distribution score is calculated based on the number of scattered point azimuth gaps and the total number of scattered points whose forward position difference from the front and rear points is less than or equal to the radar rotation azimuth.

2. A radar condensation point quality assessment method according to claim 1, characterized in that: In step S1, the specific formula for calculating the discrete degree evaluation score of the attribute according to the standard deviation of the attribute includes: in, G x Assess the score for the degree of dispersion of the attribute; S x is the standard deviation of the attribute; k1 is the coefficient.

3. A radar condensation point quality assessment method according to claim 2, characterized in that: In step S1, the specific formula for obtaining the attribute discreteness score by weighted summing of different attributes according to the attribute importance includes: G1=x1*G dis +x2*G dpl +x3*G azi +x4*G amp +x5*G tle in, G1 is the attribute dispersion score; G dis Assess the score for distance dispersion; G dpl It is the Doppler discrete range assessment score; G azi Assess the score for the degree of orientation dispersion; G amp Assess the score for the amplitude dispersion; G tle Assess the score for pitch dispersion; x1, x2, x3, x4, x5 are weighting coefficients.

4. The radar condensation point quality assessment method according to claim 1, characterized in that: In step S2, the specific formula for calculating the orientation distribution score includes: in, G2 is the orientation distribution score; m is the number of scatter azimuth gaps where the forward position difference of the forward and backward points is less than or equal to the radar rotation azimuth; n is the total number of scattered points; k2 is the coefficient.

5. The radar condensation point quality assessment method according to claim 1, characterized in that: In step S2, the minimum number of scattered points is 1 and the maximum number of scattered points is 30 according to engineering experience.

6. A radar condensation point quality assessment system, characterized in that: The system comprises: The first processing module is configured to evaluate the discrete degree of the point trace attribute: use the attribute value of the point trace to calculate the standard deviation of the attribute, and then calculate the discrete degree evaluation score of the attribute according to the standard deviation of the attribute; then perform weighted summation on different attributes according to the importance of the attribute to obtain the attribute discrete degree score; the attributes of the point trace include: distance, azimuth, Doppler, amplitude and pitch; the discrete degree of the attribute includes: distance discrete degree, azimuth discrete degree, Doppler discrete degree, amplitude discrete degree and pitch discrete degree; The second processing module is configured to: evaluate the azimuth distribution: calculate the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth; The third processing module is configured to: evaluate the number of traces: take the minimum number of scattered points and the maximum number of scattered points according to engineering experience, and then apply the method of step S1 to calculate the number of traces score; A fourth processing module is configured to add the attribute discreteness score, the orientation distribution score and the point trace quantity score to obtain a total point trace quality score; The second processing module 102 is configured to calculate the azimuth distribution score based on the forward position difference of the front and rear points being less than or equal to the number of scattered point azimuth gaps and the total number of scattered points of the radar rotation azimuth, specifically including: obtaining the radar rotation azimuth during this period of time according to the radar rotation speed and the time gap between radar frames; forming a scattered point list of condensed points, sorting the scattered points in ascending order according to the azimuth, and if the number of scattered points n is greater than 2, calculating the forward position difference of the front and rear points between the current point and the next point; and calculating the azimuth distribution score based on the number of scattered point azimuth gaps and the total number of scattered points of the front and rear points being less than or equal to the radar rotation azimuth.

7. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps in the radar condensation point quality assessment method described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the radar condensation point quality assessment method described in any one of claims 1 to 5 are implemented.

Images