A calibration coefficient determination method and device applied to a millimeter wave radar

Abstract

The application discloses a calibration coefficient determination method and device applied to a millimeter wave radar. The method comprises the following steps: determining a candidate coefficient index in a current detection period; the candidate coefficient index is used for counting the number of candidate calibration coefficients; if the candidate coefficient index is smaller than a preset coefficient index, determining to-be-processed detection data from a plurality of groups of detection data corresponding to the current detection period; processing the to-be-processed detection data to obtain a candidate calibration coefficient corresponding to the current detection period; updating the candidate coefficient index; if the updated candidate coefficient index is greater than the preset coefficient index, performing calibration coefficient evaluation on a plurality of candidate calibration coefficients based on standard channel data to obtain a coefficient evaluation result; and determining a target calibration coefficient from the plurality of candidate calibration coefficients based on the coefficient evaluation result. The application can automatically generate a calibration coefficient in the radar operation process, and can determine a target calibration coefficient from a plurality of calibration coefficients, thereby improving the reliability of target calibration coefficient determination.

Description

Technical Field

[0001] This invention relates to the field of radar technology, specifically to a method and apparatus for determining calibration coefficients for millimeter-wave radar. Background Technology

[0002] Before deployment, millimeter-wave traffic radar requires precise calibration of its array antenna, typically due to unavoidable offsets in the hardware's structural design. To address this, calibration coefficients are usually pre-generated using near-field methods in an anechoic chamber or far-field methods outdoors. However, once millimeter-wave radar is installed outdoors, prolonged exposure to sunlight can cause uneven deformation of the radome. This alters the phase difference between channels, weakening the effectiveness of the calibration coefficients and consequently affecting the radar's detection performance.

[0003] Currently, most existing millimeter-wave radars lack real-time or automatic calibration capabilities. They require stopping the millimeter-wave traffic radar, manually completing the calibration, and then restarting the radar. This makes them unable to adapt to continuously changing operating conditions and results in inconvenient calibration coefficient updates and low reliability. Summary of the Invention

[0004] In view of the above-mentioned deficiencies of the prior art, the technical problem to be solved by the present invention is how to improve the effectiveness, convenience and reliability of determining the calibration coefficient of millimeter-wave radar without hindering the normal operation of millimeter-wave radar.

[0005] To address at least one of the aforementioned technical problems, this invention discloses a method and apparatus for determining calibration coefficients for millimeter-wave radar.

[0006] According to one aspect of this disclosure, a method for determining calibration coefficients for millimeter-wave radar is provided, comprising:

[0007] Determine the candidate coefficient index for the current detection cycle; the candidate coefficient index is used to count the number of existing candidate calibration coefficients.

[0008] Determine the quantitative relationship between the candidate coefficient index and the preset coefficient index;

[0009] If the candidate coefficient index is less than the preset coefficient index, then the test data to be processed is determined from the multiple sets of test data corresponding to the current test cycle, so as to obtain the candidate calibration coefficient corresponding to the current test cycle based on the test data to be processed.

[0010] Update the candidate coefficient index;

[0011] If the updated candidate coefficient index is greater than the preset coefficient index, then the calibration coefficients of multiple candidate calibration coefficients are evaluated based on the standard channel data to obtain the coefficient evaluation result.

[0012] Based on the coefficient evaluation results, the target calibration coefficient is determined from the plurality of candidate calibration coefficients.

[0013] In some possible embodiments, if the candidate coefficient index is less than a preset coefficient index, then the detection data to be processed is determined from multiple sets of detection data corresponding to the current detection cycle, including:

[0014] Based on the first screening condition, multiple sets of detection data corresponding to the current detection cycle are filtered to obtain the first screening result; the first screening condition is a screening condition based on the distance parameter and the speed parameter.

[0015] If at least one set of detection data in the first screening results satisfies the first screening condition, the number of the at least one set of detection data is determined.

[0016] The detection data to be processed is determined based on the number of the at least one set of detection data and the preset detection quantity.

[0017] In some possible embodiments, determining the detection data to be processed based on the number of the at least one set of detection data and a preset detection number includes:

[0018] Determine the quantitative relationship between the quantity of the at least one set of detection data and the preset detection quantity;

[0019] If the number of the at least one set of detection data is greater than the preset detection number, then based on the first signal-to-noise ratio in each set of detection data, the at least one set of detection data is sorted in descending order to obtain a first data sequence;

[0020] Based on the preset number of detections, the detection data to be processed is determined from the first data sequence.

[0021] In some possible embodiments, the method further includes:

[0022] If the number of the at least one set of detection data is less than the preset detection number, then based on the second filtering condition, the multiple sets of detection data corresponding to the current detection cycle are filtered to obtain the second filtering result; the second filtering condition is a filtering condition based on the distance parameter and the speed parameter;

[0023] Based on the first signal-to-noise ratio corresponding to the detection data included in the second screening result, the detection data included in the second screening result are sorted in descending order to obtain the second data sequence;

[0024] The detection data to be processed is determined based on the preset detection quantity, the first data sequence, and the second data sequence.

[0025] In some possible embodiments, obtaining the candidate calibration coefficients corresponding to the current detection cycle based on the detection data to be processed includes:

[0026] Perform Fourier transform on the distance parameter and velocity parameter corresponding to each detection target to obtain the channel data corresponding to each detection target;

[0027] Based on the channel data corresponding to each detection target, the first dimension index, and the second dimension index, a channel data matrix including multiple detection targets is constructed.

[0028] Based on the channel data matrix, phase alignment processing is performed on the channel data corresponding to each detection target to obtain a calibration coefficient list; the calibration coefficient list includes the calibration coefficients corresponding to each detection target.

[0029] The calibration coefficient list is processed to obtain the candidate calibration coefficients corresponding to the current detection cycle.

[0030] In some possible embodiments, processing the calibration coefficient list to obtain the candidate calibration coefficients corresponding to the current detection cycle includes:

[0031] Based on the candidate calibration coefficients, data compensation is performed on the channel data of each detected target in the channel data matrix to obtain the compensated channel data;

[0032] Perform a Fourier transform on the compensated channel data to obtain multiple first spatial spectra corresponding to each detection target; each first spatial spectrum includes a second signal-to-noise ratio;

[0033] Based on a preset signal-to-noise ratio, the signal-to-noise ratio to be processed is determined from the second signal-to-noise ratios included in each first spatial spectrum;

[0034] The signal-to-noise ratio to be processed is averaged to obtain multiple average signal-to-noise ratios corresponding to each detection target.

[0035] The detection target corresponding to the maximum value among the multiple signal-to-noise ratio averages is determined, and the corresponding calibration coefficient is the candidate calibration coefficient.

[0036] In some possible embodiments, if the updated candidate coefficient index is greater than the preset coefficient index, then the multiple candidate calibration coefficients are evaluated based on standard channel data to obtain a coefficient evaluation result, including:

[0037] Based on each candidate calibration coefficient, the standard channel data is compensated to obtain the compensated standard channel data.

[0038] Perform a Fourier transform on the compensated standard channel data to obtain multiple second spatial spectra; each second spatial spectrum includes a third signal-to-noise ratio.

[0039] Based on the third signal-to-noise ratio included in each second spatial spectrum, the plurality of candidate calibration coefficients are sorted in descending order to obtain a third data sequence;

[0040] Based on the third data sequence, the calibration coefficients are evaluated to obtain multiple coefficient evaluation results corresponding to the multiple candidate calibration coefficients.

[0041] According to a second aspect of this disclosure, a calibration coefficient determination apparatus for millimeter-wave radar is provided, the apparatus comprising:

[0042] The indicator acquisition module is used to determine the candidate coefficient indicators within the current detection cycle; the candidate coefficient indicators are used to count the number of existing candidate calibration coefficients.

[0043] The indicator judgment module is used to determine the quantitative relationship between the candidate coefficient indicators and the preset coefficient indicators;

[0044] The data determination module is used to determine the test data to be processed from multiple sets of test data corresponding to the current test cycle if the candidate coefficient index is less than the preset coefficient index, so as to obtain the candidate calibration coefficient corresponding to the current test cycle based on the test data to be processed.

[0045] The indicator update module is used to update the candidate coefficient indicators;

[0046] The coefficient evaluation module is used to evaluate the calibration coefficients of multiple candidate calibration coefficients based on standard channel data if the updated candidate coefficient index is greater than the preset coefficient index, and obtain the coefficient evaluation result.

[0047] A coefficient determination module is used to determine a target calibration coefficient from the plurality of candidate calibration coefficients based on the coefficient evaluation results.

[0048] According to a third aspect of this disclosure, an electronic device is provided, the device including a processor and a memory, the memory storing at least one instruction and at least one program, the at least one instruction and the at least one program being loaded and executed by the processor to implement the calibration coefficient determination method for millimeter-wave radar as described above.

[0049] According to a fourth aspect of this disclosure, a computer storage medium is provided that stores at least one instruction and at least one program, the at least one instruction and the at least one program being loaded and executed by a processor to implement the calibration coefficient determination method for millimeter-wave radar as described above.

[0050] Implementing this invention has the following beneficial effects:

[0051] In this invention, candidate coefficient indicators are acquired in each detection cycle, ensuring that the number of candidate calibration coefficients is suitable for coefficient evaluation. This guarantees the accuracy and reliability of coefficient evaluation while avoiding resource waste caused by storing too much data simultaneously. Furthermore, if the number of candidate calibration coefficients is insufficient, candidate calibration coefficients are acquired based on multiple sets of detection data in the current detection cycle, ensuring the reliability and real-time nature of candidate calibration coefficient generation. If the number of candidate calibration coefficients meets the requirements for coefficient evaluation, calibration coefficient evaluation is performed, and the target calibration coefficient is determined based on the evaluation results. Determining a target calibration coefficient based on multiple candidate calibration coefficients improves the effectiveness and reliability of calibration coefficient determination. Additionally, since the method disclosed in this invention generates and determines calibration coefficients during the operation of the millimeter-wave radar, calibration coefficients can be generated and updated without affecting the operation of the millimeter-wave radar, thereby improving the convenience, effectiveness, and real-time nature of calibration coefficient generation. Attached Figure Description

[0052] To more clearly illustrate the technical solution of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a flowchart illustrating the calibration coefficient determination method provided in this embodiment of the invention.

[0054] Figure 2 This is a schematic diagram illustrating the process for determining the detection data to be processed, as provided in this embodiment of the invention.

[0055] Figure 3 This is a schematic diagram of the process for determining candidate coefficients provided in an embodiment of the present invention;

[0056] Figure 4 A schematic diagram of the process for evaluating calibration coefficients is provided for embodiments of the present invention;

[0057] Figure 5 This is a schematic diagram of the calibration coefficient determination device provided in an embodiment of the present invention. Detailed Implementation

[0058] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0059] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0060] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0061] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0062] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0063] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0064] Figure 1 This diagram illustrates a flowchart of a calibration coefficient determination method for millimeter-wave radar provided in an embodiment of the present invention. The executing entity can be any processor or mobile terminal capable of implementing the calibration coefficient determination method, such as a vehicle body processor included in a vehicle equipped with millimeter-wave radar. Please refer to [link to relevant documentation]. Figure 1 A method for determining calibration coefficients for millimeter-wave radar, comprising:

[0065] Step S101: Determine the candidate coefficient index within the current detection cycle; the candidate coefficient index is used to count the number of existing candidate calibration coefficients;

[0066] In one feasible embodiment, during operation, the millimeter-wave traffic radar performs signal processing once per radar frame cycle, which may include detection, angle measurement, and tracking. During the angle measurement phase, automatic channel calibration of the millimeter-wave traffic radar is achieved. The angle measurement phase can be divided into four states: idle, calibration coefficient generation, calibration coefficient evaluation, and calibration coefficient selection and activation. During operation, the millimeter-wave radar completes processing only once in one of these four states per cycle, and can perform calculations for all states within a certain timeframe, which can be as short as four consecutive cycles.

[0067] Furthermore, to ensure that the determination of calibration coefficients is supported by sufficient data, thereby improving the accuracy of the target calibration coefficient determination, and at the same time avoiding resource waste caused by excessive data storage and processing, a preset coefficient index parameter can be set in advance to determine whether it is necessary to continue acquiring candidate calibration coefficients. At the same time, a candidate coefficient index parameter is set to count the number of existing candidate calibration coefficients. By judging whether the candidate coefficient index in the current detection cycle is greater than the preset coefficient index, it can be determined whether the current detection cycle in the angle measurement stage needs to generate candidate calibration coefficients or determine the target calibration coefficient.

[0068] Step S102: Determine the quantitative relationship between the candidate coefficient index and the preset coefficient index;

[0069] Specifically, since the number of candidate calibration coefficients needs to reach a preset coefficient index in order to determine the target calibration coefficient from multiple candidate calibration coefficients, it is necessary to determine the next process by the quantitative relationship between the candidate coefficient index and the preset coefficient index.

[0070] Step S103: If the candidate coefficient index is less than the preset coefficient index, then determine the detection data to be processed from the multiple sets of detection data corresponding to the current detection cycle, so as to obtain the candidate calibration coefficient corresponding to the current detection cycle based on the detection data to be processed.

[0071] In a specific embodiment, if the candidate coefficient index is less than the preset coefficient index, it indicates that the number of candidate calibration coefficients does not meet the conditions for determining the target calibration coefficient, and it is necessary to continue to acquire candidate calibration coefficients. The generation of candidate calibration coefficients is related to the detection data within a detection cycle, and the millimeter-wave radar can detect multiple detection targets within a detection cycle, thereby generating multiple sets of detection data. Therefore, in order to generate candidate calibration coefficients, it is necessary to acquire multiple sets of detection data within the current detection cycle, and then determine the detection data to be processed from the multiple sets of detection data. The number of detection data to be processed is usually greater than one set.

[0072] In another embodiment, if the candidate coefficient index is greater than the preset coefficient index, it means that the number of candidate calibration coefficients has met the conditions required to determine the target calibration coefficient. Then, steps S104 and S106-S107 can be executed to evaluate the multiple candidate calibration coefficients, and then the target calibration coefficient can be determined based on the coefficient evaluation results.

[0073] In a specific embodiment, the detection data to be processed is processed to generate candidate calibration coefficients corresponding to the current detection cycle. The specific process is described in detail in steps S301-S304 below, and will not be repeated here.

[0074] Step S104: Update the candidate coefficient index;

[0075] In a specific embodiment, after generating the candidate calibration coefficients corresponding to the current detection period, it is necessary to update the candidate coefficient index. After generating the candidate calibration coefficients within a detection period, the method for updating the candidate coefficient index can be: updated candidate coefficient index = candidate coefficient index + 1, where the initial value of the candidate coefficient index is 0.

[0076] Step S105: Determine the quantitative relationship between the updated candidate coefficient indicators and the preset coefficient indicators;

[0077] Step S106: If the updated candidate coefficient index is greater than the preset coefficient index, then the calibration coefficients of multiple candidate calibration coefficients are evaluated based on the standard channel data to obtain the coefficient evaluation result.

[0078] Furthermore, if the updated candidate coefficient index is greater than the preset coefficient index, it indicates that the number of candidate calibration coefficients has met the conditions required for determining the target calibration coefficient. Then, based on the standard channel data, the multiple candidate calibration coefficients are evaluated to obtain the coefficient evaluation result. The calibration coefficient evaluation process is described in detail in steps S401-S404, and will not be repeated here. The standard channel data is determined based on test data collected by the millimeter-wave radar during the data frame period.

[0079] In another specific embodiment, if the updated candidate coefficient index is still less than the preset coefficient index, the execution is terminated, and the process waits for the next detection cycle. The next detection cycle is determined as the current detection cycle, and steps S101-S103 are executed to obtain the candidate calibration coefficients corresponding to the next detection cycle. After obtaining the candidate calibration coefficients, steps S104 and S105 are executed to determine whether the updated candidate coefficient index is greater than the preset coefficient index. Based on the quantitative relationship between the updated candidate coefficient index and the preset coefficient index, steps S106 and S107 are executed, or the execution is terminated. Meanwhile, since the current detection cycle has already determined that the updated candidate coefficient index is less than the preset coefficient index, steps S101 and S102 can be omitted in the next detection cycle, and step S103 can be executed directly, that is, the candidate calibration coefficients are obtained directly.

[0080] Step S107: Based on the coefficient evaluation results, determine the target calibration coefficient from the plurality of candidate calibration coefficients.

[0081] In a specific embodiment, the coefficient evaluation result may include the evaluation score corresponding to each candidate calibration coefficient. Based on the multiple evaluation scores corresponding to multiple candidate calibration coefficients, when the number of times the calibration coefficient is evaluated is greater than the preset number of evaluations, the candidate calibration coefficient corresponding to the highest value among the evaluation scores at this time is selected as the target calibration coefficient.

[0082] In this embodiment of the invention, candidate coefficient indicators are acquired in each detection cycle, ensuring that the number of candidate calibration coefficients is suitable for coefficient evaluation. This guarantees the accuracy and reliability of coefficient evaluation while avoiding resource waste caused by storing too much data simultaneously. Furthermore, if the number of candidate calibration coefficients is insufficient, candidate calibration coefficients are acquired based on multiple sets of detection data in the current detection cycle, ensuring the reliability and real-time nature of candidate calibration coefficient generation. If the number of candidate calibration coefficients meets the requirements for coefficient evaluation, calibration coefficient evaluation is performed, and a target calibration coefficient is determined based on the evaluation results. Determining a target calibration coefficient based on multiple candidate calibration coefficients improves the effectiveness and reliability of calibration coefficient determination. Additionally, since the method disclosed in this invention generates and determines calibration coefficients during the operation of the millimeter-wave radar, calibration coefficients can be generated and updated without affecting the operation of the millimeter-wave radar, thereby improving the convenience, effectiveness, and real-time nature of calibration coefficient generation.

[0083] Each set of detection data corresponds to a detection target, and the motion state of the detection target can be either in motion or at rest; each set of detection data can include at least distance parameters, velocity parameters, and a first signal-to-noise ratio. Figure 2 This is a flowchart illustrating the process of determining the corresponding detection data to be processed, as provided in this embodiment of the invention; please refer to... Figure 2 If the candidate coefficient index is less than the preset coefficient index, then the detection data to be processed is determined from the multiple sets of detection data corresponding to the current detection cycle, including:

[0084] Step S201: Based on the first filtering condition, perform data filtering on multiple sets of detection data corresponding to the current detection cycle to obtain the first filtering result; the first filtering condition is a filtering condition based on the distance parameter and the speed parameter;

[0085] In a feasible embodiment, the first screening condition may be: 30 < distance parameter < 500, and speed parameter greater than 5; based on the first screening condition and the distance parameter and speed parameter included in each set of detection data, data screening is performed in multiple sets of detection data to obtain the first screening result; wherein, the first screening result includes detection data that meets the first screening condition, and based on the first screening condition, detection targets in motion can be screened out.

[0086] Step S202: If at least one set of detection data in the first screening results satisfies the first screening condition, determine the number of the at least one set of detection data;

[0087] In a specific embodiment, if at least one set of detection data in the first screening result satisfies the first screening condition, the number of detection data that satisfies the first screening condition is first determined, and then different methods are selected based on the number of detection data to determine the detection data to be processed.

[0088] In another specific embodiment, if no detection data that meets the first screening condition is found in the first screening result, the execution is terminated and the process waits for the next cycle to be executed again.

[0089] Step S203: Determine the detection data to be processed based on the number of the at least one set of detection data and the preset detection quantity.

[0090] In one specific embodiment, step S203 may include:

[0091] Determine the quantitative relationship between the quantity of the at least one set of detection data and the preset detection quantity;

[0092] Specifically, since different methods need to be selected to determine the detection data to be processed based on the quantity of detection data, it is first necessary to determine the quantitative relationship between the quantity of at least one set of detection data and the preset detection quantity. The preset detection quantity can be customized and can be changed according to different test conditions and the working conditions of the millimeter-wave radar. In this invention, the preset detection quantity can be set to 10.

[0093] If the number of the at least one set of detection data is greater than the preset detection number, then based on the first signal-to-noise ratio in each set of detection data, the at least one set of detection data is sorted in descending order to obtain a first data sequence;

[0094] Based on the preset number of detections, the detection data to be processed is determined from the first data sequence.

[0095] If the number of at least one set of detection data is greater than the preset detection quantity, then each set of detection data is sorted in descending order according to the first signal-to-noise ratio included therein to obtain a first data sequence. Then, according to the order of each set of detection data in the first data sequence, the number of detection data in the first data sequence that is equal to the preset detection quantity is selected as the detection data to be processed.

[0096] In a specific embodiment, at least one set of detection data can be m1-m12, a total of 12 sets, and the preset detection quantity can be 10. The first signal-to-noise ratio included in each set of detection data can be s1-s12, and the order of magnitude is s1>s5>s7>s9>s11>s12>s10>s2>s4>s6>s8>s3. Then the first data sequence can be m1, m5, m7, m9, m11, m12, m10, m2, m4, m6, m8, m3 in descending order. The detection data to be processed is the first 10 selected from the first data sequence, namely m1, m5, m7, m9, m11, m12, m10, m2, m4, m6.

[0097] In another specific embodiment, step S203 may further include:

[0098] Determine the quantitative relationship between the quantity of the at least one set of detection data and the preset detection quantity;

[0099] If the number of the at least one set of detection data is less than the preset detection number, then based on the second filtering condition, the multiple sets of detection data corresponding to the current detection cycle are filtered to obtain the second filtering result; the second filtering condition is a filtering condition based on the distance parameter and the speed parameter;

[0100] If the number of at least one set of detection data is less than the preset detection quantity, it means that more detection data needs to be added to meet the preset detection quantity. At this time, a second screening condition is introduced. The second screening condition can be 30 < distance parameter < 500, and the speed parameter is 0. Based on the second screening condition and the distance parameter and speed parameter included in each set of detection data, data is screened in multiple sets of detection data to obtain the second screening result. The second screening result includes detection data that meet the second screening condition. Based on the second screening condition, detection targets in a stationary state can be screened out.

[0101] Based on the first signal-to-noise ratio corresponding to the detection data included in the second screening result, the detection data included in the second screening result are sorted in descending order to obtain the second data sequence;

[0102] The detection data to be processed is determined based on the preset detection quantity, the first data sequence, and the second data sequence.

[0103] The detection data included in the second screening result are sorted in descending order according to the first signal-to-noise ratio to obtain a second data sequence. Then, according to the order of each group of detection data in the second data sequence, a number of detection data equal to the difference between the preset number of detections and the number of at least one group of detection data is selected from the second data sequence, and together with at least one group of detection data, they are used as the detection data to be processed.

[0104] In a specific embodiment, at least one set of detection data can be a1-a4, a total of 4 sets, and the corresponding first signal-to-noise ratio can be n1-n4; the second screening result includes detection data b1-b9, a total of 9 sets, and the corresponding first signal-to-noise ratio can be r1-r9, with the order r1>r5>r7>r9>r2>r4>r6>r8>r3; the preset detection quantity can be 10; then the second data sequence can be b1, b5, b7, b9, b2, b4, b6, b8, b3 in descending order. The number of detection data to be processed needs to be determined from the second data sequence as the preset detection quantity minus the number of at least one set of detection data, i.e., 10-4. Therefore, the first 6 data are selected from the second data sequence, i.e., b1, b5, b7, b9, b2, b4; finally, the detection data to be processed are a1-a4 and b1, b5, b7, b9, b2, b4, a total of 10.

[0105] In this embodiment of the invention, by combining detection data, preset detection quantity, and multiple screening conditions, the detection data used to generate candidate calibration coefficients can be guaranteed to be reliable and effective; and multiple screening conditions can ensure that sufficient detection data is obtained under different conditions, thus ensuring data richness and further improving the reliability and effectiveness of candidate calibration coefficient generation.

[0106] In addition to the distance parameter, velocity parameter, and first signal-to-noise ratio, each set of detection data also includes the first dimension index corresponding to the distance parameter and the second dimension index corresponding to the velocity parameter. Figure 3 This diagram illustrates the process for determining candidate coefficients provided in an embodiment of the present invention.

[0107] Please see Figure 3 The step of obtaining the candidate calibration coefficients corresponding to the current detection cycle based on the detection data to be processed includes:

[0108] Step S301: Perform Fourier transform on the distance parameter and velocity parameter corresponding to each detection target to obtain the channel data corresponding to each detection target;

[0109] In one feasible embodiment, the number of array elements in the virtual antenna array of the millimeter-wave radar is N, and the number of targets detected in one detection period is M. Then, the number of channel data in one detection period can be M*N; the channel data can be the phase information of each array element in the virtual antenna array.

[0110] Furthermore, Fourier transform is performed based on the distance and velocity parameters corresponding to each detected target to obtain the channel data corresponding to each detected target. The number of channels may include multiple phase information corresponding to one detected target and multiple array elements.

[0111] Step S302: Based on the channel data corresponding to each detection target, the first dimension index, and the second dimension index, construct a channel data matrix including multiple detection targets;

[0112] In one feasible embodiment, the position of each channel data in the channel data matrix is ​​determined based on the first dimension index and the second dimension index, and then the channel data matrix is ​​generated based on the channel data and the radial distance; wherein, the radial distance is the distance between the corner reflector and the millimeter-wave radar.

[0113] Channel data matrix D ij In the diagram, i = (1, 2, ..., M), M is the number of detected targets, and the maximum value of M can be a preset number of targets; j = (1, 2, ..., N), N is the number of array elements in the virtual antenna array; the channel data matrix D... ij In the middle, D 11 For the channel data corresponding to the first detected target and the first array element, D 1M This refers to the channel data corresponding to the first detection target and each array element.

[0114] ;

[0115] Step S303: Based on the channel data matrix, perform phase alignment processing on the channel data corresponding to each detection target to obtain a calibration coefficient list; the calibration coefficient list includes the calibration coefficients corresponding to each detection target;

[0116] In one specific embodiment, the difference between the channel data of each target and its first channel data is phase aligned. Phase alignment can be achieved by performing conjugate multiplication on the multiple channel data of each detected target and its corresponding first channel data, where the first channel data is not processed. Then, normalization is performed to obtain C. ij That is, C 11 =D 11 C 12= =D 11 *D 12 C 1j= =D 11 *D 1j C ij= =D i1 *D ij The resulting matrix C ij as follows:

[0117] ;

[0118] Step S304: Process the calibration coefficient list to obtain the candidate calibration coefficients corresponding to the current detection cycle.

[0119] In one specific embodiment, step S304 may include:

[0120] Based on the candidate calibration coefficients, data compensation is performed on the channel data of each detected target in the channel data matrix to obtain the compensated channel data;

[0121] Perform a Fourier transform on the compensated channel data to obtain multiple first spatial spectra corresponding to each detection target; each first spatial spectrum includes a second signal-to-noise ratio;

[0122] In one specific embodiment, C is used. ij Each calibration coefficient in D ij Data compensation is performed on the channel data corresponding to each detection, and then a fast Fourier transform is performed on the compensated data to obtain multiple first spatial spectra corresponding to each detection target; the second signal-to-noise ratio corresponding to each detection target can be determined by analyzing the first spatial spectra.

[0123] Based on a preset signal-to-noise ratio, the signal-to-noise ratio to be processed is determined from the second signal-to-noise ratios included in each first spatial spectrum;

[0124] In one specific embodiment, the preset signal-to-noise ratio can be changed based on user needs. In this invention, the preset signal-to-noise ratio can be 12. Each second signal-to-noise ratio is compared with the preset signal-to-noise ratio, and the second signal-to-noise ratio that is greater than the preset signal-to-noise ratio is determined as the signal-to-noise ratio to be processed. The number of signal-to-noise ratios to be processed is usually multiple.

[0125] The signal-to-noise ratio to be processed is averaged to obtain multiple average signal-to-noise ratios corresponding to each detection target.

[0126] The detection target corresponding to the maximum value among the multiple signal-to-noise ratio averages is determined, and the corresponding calibration coefficient is the candidate calibration coefficient.

[0127] In an optional embodiment, the mean value corresponding to each signal-to-noise ratio to be processed is calculated separately, and the mean value processing formula is as follows:

[0128] ;

[0129] Where SNR is the signal-to-noise ratio to be processed; according to the mean processing formula, multiple mean SNR values ​​are obtained respectively, such as meanSNR2 representing the calibration coefficient generated by the second target relative to D. ij After processing each target, the average signal-to-noise ratio is obtained. The detection target corresponding to the maximum value among multiple average signal-to-noise ratios is determined, and the corresponding calibration coefficient is the candidate calibration coefficient. At the same time, the candidate coefficient index is updated.

[0130] In this embodiment of the invention, performing operations such as phase alignment, data compensation, Fourier transform, and mean processing on the data can reduce the errors caused by the data, thereby improving the reliability of the candidate calibration coefficients.

[0131] Figure 4 This diagram illustrates the process flow for calibration coefficient evaluation provided in this embodiment of the invention; please refer to [link / reference]. Figure 4 If the updated candidate coefficient index is greater than the preset coefficient index, then the multiple candidate calibration coefficients are evaluated based on standard channel data to obtain the coefficient evaluation result, including:

[0132] Step S401: Based on each candidate calibration coefficient, perform data compensation on the standard channel data to obtain the compensated standard channel data;

[0133] In a feasible embodiment, the standard channel data is determined by the test detection data corresponding to multiple detection targets acquired within the data frame period. First, based on steps S201-S203, the test detection data to be processed is determined from the test detection data. Then, based on step S301, the channel data corresponding to the multiple detection targets is determined, which is the standard channel data.

[0134] Further, the standard channel data is compensated based on the candidate calibration coefficients determined in step S304 to obtain compensated standard channel data; wherein the detection target corresponding to the compensated standard channel data is consistent with the detection target corresponding to the candidate calibration coefficients determined in step S304.

[0135] Step S402: Perform a Fourier transform on the compensated standard channel data to obtain multiple second spatial spectra; each second spatial spectrum includes a third signal-to-noise ratio;

[0136] Step S403: Based on the third signal-to-noise ratio included in each second spatial spectrum, sort the multiple candidate calibration coefficients in descending order to obtain a third data sequence;

[0137] In one specific embodiment, the compensated standard channel data is subjected to Fourier transform to obtain a second spatial spectrum corresponding to the detection target. The spatial spectrum is then analyzed to determine the third signal-to-noise ratio corresponding to each detection target. Based on the data size of the third signal-to-noise ratio, the candidate calibration coefficients are sorted in descending order to obtain a third data sequence.

[0138] Step S404: Based on the third data sequence, perform calibration coefficient evaluation to obtain multiple coefficient evaluation results corresponding to the multiple candidate calibration coefficients.

[0139] In one specific embodiment, for candidate calibration coefficients, the one ranked first in the third data sequence has its evaluation score increased by 1 point, the one ranked second has its evaluation score increased by 0.5 points, and other candidate calibration coefficients are not processed.

[0140] In this embodiment of the invention, by scoring the candidate calibration coefficients and then determining a target calibration coefficient from multiple candidate calibration coefficients based on the coefficient evaluation results, the reliability and accuracy of the target calibration coefficient can be improved, thereby ensuring the accuracy of millimeter-wave radar operation.

[0141] This invention also provides a calibration coefficient determination device for millimeter-wave radar, such as... Figure 5 As shown, the device includes:

[0142] The indicator acquisition module 510 is used to determine the candidate coefficient indicators within the current detection cycle; the candidate coefficient indicators are used to count the number of existing candidate calibration coefficients.

[0143] Indicator judgment module 520 is used to judge the quantitative relationship between the candidate coefficient indicators and the preset coefficient indicators;

[0144] The data determination module 530 is used to determine the test data to be processed from multiple sets of test data corresponding to the current test cycle if the candidate coefficient index is less than the preset coefficient index, so as to obtain the candidate calibration coefficient corresponding to the current test cycle based on the test data to be processed.

[0145] Indicator update module 540 is used to update the candidate coefficient indicators;

[0146] The coefficient evaluation module 550 is used to evaluate the calibration coefficients of multiple candidate calibration coefficients based on standard channel data if the updated candidate coefficient index is greater than the preset coefficient index, and obtain the coefficient evaluation result.

[0147] The coefficient determination module 560 is used to determine the target calibration coefficient from the plurality of candidate calibration coefficients based on the coefficient evaluation results.

[0148] In other embodiments, the data determination module 530 further includes:

[0149] The first filtering module is used to filter multiple sets of detection data corresponding to the current detection cycle based on a first filtering condition to obtain a first filtering result; the first filtering condition is a filtering condition based on the distance parameter and the speed parameter.

[0150] The first determining module is used to determine the number of the at least one set of detection data when there is at least one set of detection data in the first filtering result that satisfies the first filtering condition;

[0151] The second determining module is used to determine the detection data to be processed based on the number of the at least one set of detection data and a preset detection number.

[0152] In other embodiments, the second determining module further includes:

[0153] The judgment module is used to determine the quantitative relationship between the quantity of the at least one set of detection data and the preset detection quantity;

[0154] The first sorting module is used to sort the at least one set of detection data in descending order based on the first signal-to-noise ratio in each set of detection data if the number of the at least one set of detection data is greater than the preset detection number, so as to obtain a first data sequence.

[0155] The third determining module is used to determine the detection data to be processed from the first data sequence based on the preset detection quantity.

[0156] In other embodiments, the device further includes:

[0157] The second filtering module is used to filter multiple sets of detection data corresponding to the current detection cycle based on a second filtering condition if the number of the at least one set of detection data is less than the preset detection quantity, thereby obtaining a second filtering result; the second filtering condition is a filtering condition based on the distance parameter and the speed parameter.

[0158] The second sorting module is used to sort the detection data included in the second screening result in descending order based on the first signal-to-noise ratio corresponding to the detection data included in the second screening result, so as to obtain a second data sequence.

[0159] The fourth determining module is used to determine the detection data to be processed based on the preset detection quantity, the first data sequence, and the second data sequence.

[0160] In other embodiments, the data determination module 530 further includes:

[0161] The data acquisition module is used to perform Fourier transform on the distance parameter and the velocity parameter corresponding to each detection target to obtain the channel data corresponding to each detection target;

[0162] The matrix construction module is used to construct a channel data matrix including multiple detection targets based on the channel data corresponding to each detection target, the first dimension index, and the second dimension index.

[0163] The phase calibration module is used to perform phase alignment processing on the channel data corresponding to each detection target based on the channel data matrix to obtain a calibration coefficient list; the calibration coefficient list includes the calibration coefficients corresponding to each detection target;

[0164] The fifth determining module is used to process the calibration coefficient list to obtain the candidate calibration coefficients corresponding to the current detection cycle.

[0165] In other embodiments, the fifth determining module further includes:

[0166] The first compensation module is used to perform data compensation on the channel data of each detection target in the channel data matrix based on the candidate calibration coefficients, so as to obtain the compensated channel data.

[0167] The first transformation module is used to perform Fourier transform on the compensated channel data to obtain multiple first spatial spectra corresponding to each detection target; each first spatial spectrum includes a second signal-to-noise ratio.

[0168] The signal-to-noise ratio (SNR) processing module is used to determine the SNR to be processed from the second SNR included in each first spatial spectrum based on a preset SNR.

[0169] The mean processing module is used to perform data averaging on the signal-to-noise ratio to be processed, and obtain multiple mean values ​​of signal-to-noise ratio corresponding to each detection target;

[0170] The sixth determining module is used to determine the detection target corresponding to the maximum value among the multiple signal-to-noise ratio averages, and the corresponding calibration coefficient is the candidate calibration coefficient.

[0171] In other embodiments, the coefficient evaluation module 550 further includes:

[0172] The second compensation module is used to perform data compensation on the standard channel data based on each candidate calibration coefficient to obtain the compensated standard channel data.

[0173] The second transformation module is used to perform Fourier transform on the compensated standard channel data to obtain multiple second spatial spectra; each second spatial spectrum includes a third signal-to-noise ratio.

[0174] The third sorting module is used to sort the multiple candidate calibration coefficients in descending order based on the third signal-to-noise ratio included in each second spatial spectrum to obtain a third data sequence;

[0175] The result determination module is used to evaluate the calibration coefficients based on the third data sequence and obtain multiple coefficient evaluation results corresponding to the multiple candidate calibration coefficients.

[0176] The apparatus and method embodiments described above are based on the same inventive concept and are used to implement the above-mentioned calibration coefficient determination method applied to millimeter-wave radar.

[0177] This invention also provides a device for determining calibration coefficients for millimeter-wave radar. The device includes a processor and a memory. The memory stores at least one instruction, at least one program, a code set, or an instruction set. The at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the calibration coefficient determination method for millimeter-wave radar as described in any of the method embodiments.

[0178] Embodiments of the present invention also provide a storage medium, which can be disposed in a server to store at least one instruction, at least one program, code set, or instruction set for implementing a calibration coefficient determination method for millimeter-wave radar as described in any of the method embodiments. The at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the calibration coefficient determination method for millimeter-wave radar as described in any of the method embodiments.

[0179] Optionally, in embodiments of the present invention, the storage medium may be located at at least one of a plurality of network servers in a computer network. Optionally, in embodiments of the present invention, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0180] As can be seen from the embodiments provided by the present invention above, in this invention, candidate coefficient indicators are acquired in each detection cycle, ensuring that the number of candidate calibration coefficients is suitable for coefficient evaluation. This ensures the accuracy and reliability of coefficient evaluation while avoiding resource waste caused by storing too much data simultaneously. Furthermore, if the number of candidate calibration coefficients is insufficient, candidate calibration coefficients are acquired based on multiple sets of detection data in the current detection cycle, ensuring the reliability and real-time nature of candidate calibration coefficient generation. If the number of candidate calibration coefficients meets the requirements for coefficient evaluation, calibration coefficient evaluation is performed, and the target calibration coefficient is determined based on the coefficient evaluation results. Determining the target calibration coefficient based on multiple candidate calibration coefficients improves the effectiveness and reliability of calibration coefficient determination. In addition, since the method disclosed in this invention generates and determines calibration coefficients during the operation of millimeter-wave radar, calibration coefficients can be generated and updated without affecting the operation of millimeter-wave radar, thereby improving the convenience, effectiveness, and real-time nature of calibration coefficient generation. Furthermore, since calibration coefficients can be automatically generated during the operation of millimeter-wave radar, the continuity and effectiveness of millimeter-wave radar operation can be ensured. Moreover, since calibration coefficients are automatically corrected to ensure their accuracy and reliability, the reliability and accuracy of millimeter-wave radar operation can be improved on this basis.

[0181] It should be noted that the various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technological improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for determining calibration coefficients for millimeter-wave radar, characterized in that, The method includes: Determine the candidate coefficient index for the current detection cycle; the candidate coefficient index is used to count the number of existing candidate calibration coefficients. Determine the quantitative relationship between the candidate coefficient index and the preset coefficient index; If the candidate coefficient index is less than the preset coefficient index, then the test data to be processed is determined from the multiple sets of test data corresponding to the current test cycle, so as to obtain the candidate calibration coefficient corresponding to the current test cycle based on the test data to be processed. Update the candidate coefficient index; If the updated candidate coefficient index is greater than the preset coefficient index, then the calibration coefficients of multiple candidate calibration coefficients are evaluated based on the standard channel data to obtain the coefficient evaluation result. Based on the coefficient evaluation results, the target calibration coefficient is determined from the plurality of candidate calibration coefficients.

2. The calibration coefficient determination method for millimeter-wave radar according to claim 1, characterized in that, Each set of detection data includes at least distance parameters, velocity parameters, and a first signal-to-noise ratio; If the candidate coefficient index is less than the preset coefficient index, then the detection data to be processed is determined from the multiple sets of detection data corresponding to the current detection cycle, including: Based on the first screening condition, multiple sets of detection data corresponding to the current detection cycle are filtered to obtain the first screening result; the first screening condition is a screening condition based on the distance parameter and the speed parameter. If at least one set of detection data in the first screening results satisfies the first screening condition, the number of the at least one set of detection data is determined. The detection data to be processed is determined based on the number of the at least one set of detection data and the preset detection quantity.

3. The calibration coefficient determination method for millimeter-wave radar according to claim 2, characterized in that, The step of determining the detection data to be processed based on the quantity of the at least one set of detection data and a preset detection quantity includes: Determine the quantitative relationship between the quantity of the at least one set of detection data and the preset detection quantity; If the number of the at least one set of detection data is greater than the preset detection number, then based on the first signal-to-noise ratio in each set of detection data, the at least one set of detection data is sorted in descending order to obtain a first data sequence; Based on the preset number of detections, the detection data to be processed is determined from the first data sequence.

4. The calibration coefficient determination method for millimeter-wave radar according to claim 3, characterized in that, The method further includes: If the number of the at least one set of detection data is less than the preset detection number, then based on the second filtering condition, the multiple sets of detection data corresponding to the current detection cycle are filtered to obtain the second filtering result; the second filtering condition is a filtering condition based on the distance parameter and the speed parameter; Based on the first signal-to-noise ratio corresponding to the detection data included in the second screening result, the detection data included in the second screening result are sorted in descending order to obtain the second data sequence; The detection data to be processed is determined based on the preset detection quantity, the first data sequence, and the second data sequence.

5. The method for determining calibration coefficients for millimeter-wave radar according to claim 1, characterized in that, Each set of detection data corresponds to one detection target; each set of detection data includes a first-dimensional index corresponding to the distance parameter and a second-dimensional index corresponding to the velocity parameter; The process of obtaining the candidate calibration coefficients corresponding to the current detection cycle based on the detection data to be processed includes: Perform Fourier transform on the distance parameter and velocity parameter corresponding to each detection target to obtain the channel data corresponding to each detection target; Based on the channel data corresponding to each detection target, the first dimension index, and the second dimension index, a channel data matrix including multiple detection targets is constructed. Based on the channel data matrix, phase alignment processing is performed on the channel data corresponding to each detection target to obtain a calibration coefficient list; the calibration coefficient list includes the calibration coefficients corresponding to each detection target. The calibration coefficient list is processed to obtain the candidate calibration coefficients corresponding to the current detection cycle.

6. The calibration coefficient determination method for millimeter-wave radar according to claim 5, characterized in that, The process of processing the calibration coefficient list to obtain the candidate calibration coefficients corresponding to the current detection cycle includes: Based on the candidate calibration coefficients, data compensation is performed on the channel data of each detected target in the channel data matrix to obtain the compensated channel data; Perform a Fourier transform on the compensated channel data to obtain multiple first spatial spectra corresponding to each detection target; each first spatial spectrum includes a second signal-to-noise ratio; Based on a preset signal-to-noise ratio, the signal-to-noise ratio to be processed is determined from the second signal-to-noise ratios included in each first spatial spectrum; The signal-to-noise ratio to be processed is averaged to obtain multiple average signal-to-noise ratios corresponding to each detection target. The detection target corresponding to the maximum value among the multiple signal-to-noise ratio averages is determined, and the corresponding calibration coefficient is the candidate calibration coefficient.

7. The calibration coefficient determination method for millimeter-wave radar according to claim 1, characterized in that, If the updated candidate coefficient index is greater than the preset coefficient index, then the multiple candidate calibration coefficients are evaluated based on standard channel data to obtain the coefficient evaluation result, including: Based on each candidate calibration coefficient, the standard channel data is compensated to obtain the compensated standard channel data. Perform a Fourier transform on the compensated standard channel data to obtain multiple second spatial spectra; each second spatial spectrum includes a third signal-to-noise ratio. Based on the third signal-to-noise ratio included in each second spatial spectrum, the plurality of candidate calibration coefficients are sorted in descending order to obtain a third data sequence; Based on the third data sequence, the calibration coefficients are evaluated to obtain multiple coefficient evaluation results corresponding to the multiple candidate calibration coefficients.

8. A calibration coefficient determination device for millimeter-wave radar, characterized in that, The device includes: The indicator acquisition module is used to determine the candidate coefficient indicators within the current detection cycle; the candidate coefficient indicators are used to count the number of existing candidate calibration coefficients. The indicator judgment module is used to determine the quantitative relationship between the candidate coefficient indicators and the preset coefficient indicators; The data determination module is used to determine the test data to be processed from multiple sets of test data corresponding to the current test cycle if the candidate coefficient index is less than the preset coefficient index, so as to obtain the candidate calibration coefficient corresponding to the current test cycle based on the test data to be processed. The indicator update module is used to update the candidate coefficient indicators; The coefficient evaluation module is used to evaluate the calibration coefficients of multiple candidate calibration coefficients based on standard channel data if the updated candidate coefficient index is greater than the preset coefficient index, and obtain the coefficient evaluation result. A coefficient determination module is used to determine a target calibration coefficient from the plurality of candidate calibration coefficients based on the coefficient evaluation results.

9. An electronic device, the device comprising a processor and a memory, the memory storing at least one instruction and at least one program, characterized in that, The at least one instruction and the at least one program segment are loaded and executed by the processor to implement the calibration coefficient determination method for millimeter-wave radar as described in any one of claims 1-7.

10. A computer storage medium storing at least one instruction and at least one program, characterized in that, The at least one instruction and the at least one program segment are loaded and executed by the processor to implement the calibration coefficient determination method for millimeter-wave radar as described in any one of claims 1-7.

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