A millimeter-wave high-precision ranging method based on precise chirp delay

Abstract

The present invention provides a millimeter-wave high-precision ranging method based on precise chirp delay, including: Step 1: Obtain the echo signal received by the millimeter-wave radar when ranging a target object; Step 2: Based on the echo signal and a preset original chirp signal, construct a first intermediate-frequency signal; Step 3: Based on the first intermediate-frequency signal, determine the coarse-grained estimated ranging interval of the target object; Step 4: Based on the estimated ranging interval, determine the delay T d ; Step 5: Based on the echo signal and the delayed chirp signal delayed by T relative to the original chirp signal d , construct a second intermediate-frequency signal; Step 6: Based on the second intermediate-frequency signal, determine the fine-grained target distance of the target object. The millimeter-wave high-precision ranging method based on precise chirp delay of the present invention improves the ranging accuracy.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and particularly to a high-precision millimeter-wave ranging method based on precise chirp delay. Background Art

[0002] Currently, in the measurement principle and engineering implementation of traditional millimeter waves, the actual ranging accuracy is limited by the resolution of Rangebin, which is fundamentally due to the insufficient frequency analysis ability of the intermediate-frequency signal. However, because the frequency components of the intermediate-frequency signal generated by the millimeter-wave analog front-end are ultimately limited, the ranging accuracy cannot be infinitely refined. Currently, only rangebin is used for ranging, and the accuracy can only reach coarse ranging (generally centimeter level).

[0003] Therefore, a solution is urgently needed. Summary of the Invention

[0004] One of the purposes of the present invention is to provide a high-precision millimeter-wave ranging method based on precise chirp delay. First, coarse ranging is performed to determine the approximate position of the target object. According to the approximate position, a delayed chirp is determined, and a new intermediate frequency is constructed with the echo. Based on the new intermediate frequency, fine-grained ranging is performed on the approximate position, improving the ranging accuracy.

[0005] A high-precision millimeter-wave ranging method based on precise chirp delay provided by an embodiment of the present invention includes:

[0006] Step 1: Obtain the echo signal received when a millimeter-wave radar ranges a target object;

[0007] Step 2: Based on the echo signal and a preset original chirp signal, construct a first intermediate-frequency signal;

[0008] Step 3: Based on the first intermediate-frequency signal, determine the coarse-grained estimated ranging interval of the target object;

[0009] Step 4: Based on the estimated ranging interval, determine the delay T d ;

[0010] Step 5: Based on the echo signal and a delayed chirp signal delayed by the delay T relative to the original chirp signal d construct a second intermediate-frequency signal;

[0011] Step 6: Based on the second intermediate-frequency signal, determine the fine-grained target distance of the target object.

[0012] Preferably, in step 2: Based on the echo signal and a preset original chirp signal, construct a first intermediate-frequency signal, including:

[0013] Based on a preset first construction rule, a first intermediate frequency signal is constructed according to the echo signal and a preset original chirp signal.

[0014] Preferably, step 3: determining a coarse-grained estimated ranging interval of the target based on the first intermediate frequency signal includes:

[0015] Analyzing the first intermediate frequency signal based on a preset first analysis rule to obtain a plurality of first distance values;

[0016] Using the maximum value and the minimum value among the first distance values as interval boundaries respectively to produce a coarse-grained estimated ranging interval of the target.

[0017] Preferably, step 4: determining the delay T based on the estimated ranging interval d , includes:

[0018] Constructing an interval-delay library;

[0019] Determining the delay T corresponding to the estimated ranging interval based on the interval-delay library d .

[0020] Preferably, step 5: constructing a second intermediate frequency signal based on the echo signal and a delayed chirp signal delayed by the delay T relative to the original chirp signal d includes:

[0021] Based on a preset second construction rule, constructing a second intermediate frequency signal according to the echo signal and a delayed chirp signal delayed by the delay T relative to the original chirp signal d after that.

[0022] Preferably, determining the fine-grained target distance of the target based on the second intermediate frequency signal includes:

[0023] Analyzing the second intermediate frequency signal based on a preset second analysis rule to obtain a plurality of second distance values and using them as the fine-grained target distance of the target.

[0024] Preferably, constructing the interval-delay library includes:

[0025] Obtaining a preset test interval set, where the test interval set includes: a plurality of intervals;

[0026] Obtaining a plurality of test records for performing interval appropriate delay tests corresponding to the intervals, where the test records include: test processes and test results;

[0027] Performing process splitting on the test processes to obtain a plurality of sub-processes;

[0028] Obtain a preset first feature extraction template and a process evaluation library corresponding to the process type of the sub-process;

[0029] Based on the first feature extraction template, perform feature extraction on the sub-process to obtain a plurality of first feature values;

[0030] Based on the first feature values, construct a process description factor;

[0031] Based on the process evaluation library and the process description factor, determine an evaluation value;

[0032] Obtain the process weight of the sub-process corresponding to the test process;

[0033] Assign the evaluation value the corresponding process weight to obtain a target value, and associate it with the corresponding test record;

[0034] Accumulatively calculate the target values associated with the test records to obtain a sum of target values;

[0035] Extract the delay in the test results in the test record corresponding to the maximum sum of target values;

[0036] Pair the delay with the corresponding interval to obtain a pairing item;

[0037] Obtain a preset blank database, and add the pairing item into the blank database;

[0038] After all the pairing items to be added into the blank database are added, use the blank database as an interval-delay library to complete the construction.

[0039] Preferably, the obtaining of the multiple test records for performing interval-appropriate delay testing corresponding to the interval includes:

[0040] Obtain a preset manual input library;

[0041] Determine from the manual input library the test records for performing interval-appropriate delay testing input by a first tester corresponding to the interval;

[0042] And / or,

[0043] When multiple second testers start to perform interval-appropriate delay testing, construct an online meeting room and connect all the second testers to the online meeting room;

[0044] Obtain a plurality of first conversation records generated by the testers in the online meeting room;

[0045] Based on the first conversation records, determine test records.

[0046] Preferably, determining the test record based on the first conversation record includes:

[0047] Performing semantic extraction on the first conversation record to obtain a first semantics;

[0048] Obtaining a preset irrelevant semantics library, and matching the first semantics with a second semantics in the irrelevant semantics;

[0049] If the match is successful, removing the first conversation record corresponding to the first semantics that matches successfully;

[0050] After all the first conversation records to be removed are removed, using the remaining first conversation records as the second conversation record;

[0051] Establishing a timeline;

[0052] Obtaining the generation time point of the conversation record;

[0053] Based on the generation time point, correspondingly setting the second conversation record on the timeline;

[0054] Obtaining a preset test semantics library;

[0055] Matching the first semantics corresponding to the second conversation record with a third semantics in the test semantics library;

[0056] If the match is successful, obtaining a preset item to be recorded corresponding to the third semantics that matches successfully, and at the same time, using the second conversation records before and / or after the second conversation record corresponding to the first semantics that matches successfully on the timeline as the third conversation record;

[0057] Based on the third conversation record, determining whether the item to be recorded is effective;

[0058] If so, using the corresponding item to be recorded as the target to be recorded;

[0059] Integrating each target to be recorded to obtain a test record.

[0060] Preferably, determining whether the item to be recorded is effective based on the third conversation record includes:

[0061] Obtaining a preset semantic understanding model;

[0062] Inputting the second conversation record corresponding to the first semantics that matches successfully and the third conversation record into the semantic understanding model to determine whether the item to be recorded is effective;

[0063] And / or,

[0064] Obtain the preset second feature extraction template and the effectiveness determination library corresponding to the first semantics that match when matching with the third semantics;

[0065] Based on the second feature extraction template, perform feature extraction on the first semantics corresponding to the third conversation record and the positional relationship on the time axis of the second conversation record and the third conversation record corresponding to the matching first semantics, and obtain a plurality of second feature values;

[0066] Based on the second feature values, construct a semantic description factor;

[0067] Based on the effectiveness determination library and the semantic description factor, determine whether the item to be recorded is effective.

[0068] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in the written specification, claims, and drawings.

[0069] The technical solutions of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0070] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0071] Figure 1 is a flowchart of a millimeter-wave high-precision ranging method based on precise chirp delay in an embodiment of the present invention;

[0072] Figure 2 is a schematic diagram of a millimeter-wave high-precision ranging method based on precise chirp delay in an embodiment of the present invention;

[0073] Figure 3 is another schematic diagram of a millimeter-wave high-precision ranging method based on precise chirp delay in an embodiment of the present invention. Detailed Embodiments

[0074] The following describes the preferred embodiments of the present invention with reference to the drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0075] The embodiment of the present invention provides a millimeter-wave high-precision ranging method based on precise chirp delay, as Figures 1-3 shown, including:

[0076] Step 1: Obtain the echo signal received when the millimeter-wave radar measures the distance to the target object;

[0077] Step 2: Based on the echo signal and the preset original chirp signal, construct a first intermediate-frequency signal;

[0078] Step 3: Based on the first intermediate-frequency signal, determine the coarse-grained estimated ranging interval of the target object;

[0079] Step 4: Based on the estimated ranging interval, determine the delay T d ;

[0080] Step 5: Based on the echo signal and the delayed chirp signal delayed by the delay T with respect to the original chirp signal d construct a second intermediate-frequency signal;

[0081] Step 6: Based on the second intermediate-frequency signal, determine the fine-grained target distance of the target object;

[0082] The said Step 2: Based on the echo signal and the preset original chirp signal, construct a first intermediate-frequency signal, including:

[0083] Based on the preset first construction rule, construct a first intermediate-frequency signal according to the echo signal and the preset original chirp signal;

[0084] The said Step 3: Based on the first intermediate-frequency signal, determine the coarse-grained estimated ranging interval of the target object, including:

[0085] Based on the preset first analysis rule, analyze the first intermediate-frequency signal to obtain multiple first distance values;

[0086] Take the maximum value and the minimum value among the first distance values as the interval boundaries respectively to make the coarse-grained estimated ranging interval of the target object;

[0087] The said Step 4: Based on the estimated ranging interval, determine the delay T d , including:

[0088] Construct an interval-delay library;

[0089] Based on the interval-delay library, determine the delay T corresponding to the estimated ranging interval d ;

[0090] The said Step 5: Based on the echo signal and the delayed chirp signal delayed by the delay T with respect to the original chirp signal d construct a second intermediate-frequency signal, including:

[0091] Based on a preset second construction rule, according to the echo signal and the delayed chirp signal that is delayed by the delay T relative to the original chirp signal, construct a second intermediate frequency signal; d After the delay chirp signal, construct a second intermediate frequency signal;

[0092] Determining the fine-grained target distance of the target based on the second intermediate frequency signal includes:

[0093] Based on a preset second analysis rule, analyze the second intermediate frequency signal to obtain multiple second distance values and use them as the fine-grained target distance of the target.

[0094] The working principle and beneficial effects of the above technical solution are as follows:

[0095] After using a millimeter-wave radar to scan a target, an echo signal is reflected from the target. Introduce a preset first construction rule. The first construction rule is, as Figure 2 shown, expand the echo signal and the original chirp signal in the same frequency-time coordinate system (vertical axis frequency, horizontal axis), and use the frequency difference between the radar echo signal and the original chirp in the overlapping area as the first intermediate frequency signal (intermediate frequency 1 in the figure). Based on the first construction rule, according to the echo signal and the preset original chirp signal, construct the first intermediate frequency signal. Introduce a preset first analysis rule. The first analysis rule is to perform frequency-domain analysis on the first intermediate frequency signal. The frequency points in the first intermediate frequency signal correspond to the distance from the origin to the target. Therefore, a first distance value can be obtained. This method belongs to the technical category of the existing millimeter-wave radar ranging principle. Use the maximum and minimum values in the first distance value as the interval boundaries respectively to construct an estimated ranging interval, as Figure 3 shown. Introduce an interval-delay library, which stores delay values corresponding to different estimated ranging intervals. Based on the interval-delay library, determine the delay T d . Introduce a second construction rule. The second construction rule is the same as the first construction rule. As Figure 2 shown, based on the echo signal and the delayed chirp signal, construct a second intermediate frequency signal (intermediate frequency 2 in the figure). Introduce a preset second analysis rule. The second analysis rule is the same as the first analysis rule. Based on the second analysis rule, perform frequency-domain analysis on the second intermediate frequency signal to obtain the fine-grained target distance.

[0096] This application first performs rough ranging to determine the approximate position of the target. According to the approximate position, determine the delayed chirp, construct a new intermediate frequency with the echo, and perform fine-grained ranging on the approximate position based on the new intermediate frequency, improving the ranging accuracy.

[0097] The embodiment of the present invention provides a millimeter-wave high-precision ranging method based on precise chirp delay. The construction of the interval-delay library includes:

[0098] Obtain a preset test interval set, where the test interval set includes: multiple intervals;

[0099] Obtain multiple test records for performing interval suitability delay tests corresponding to the intervals, where the test records include: test processes and test results;

[0100] Perform process splitting on the test process to obtain multiple sub-processes;

[0101] Obtain a preset first feature extraction template and a process evaluation library corresponding to the process type of the sub-process;

[0102] Based on the first feature extraction template, perform feature extraction on the sub-process to obtain multiple first feature values;

[0103] Based on the first feature values, construct a process description factor;

[0104] Based on the process evaluation library and the process description factor, determine an evaluation value;

[0105] Obtain the process weight of the sub-process corresponding to the test process;

[0106] Assign the evaluation value the corresponding process weight to obtain a target value, and associate it with the corresponding test record;

[0107] Accumulatively calculate the target values associated with the test records to obtain a sum of target values;

[0108] Extract the delay in the test result of the test record corresponding to the maximum sum of target values;

[0109] Pair the delay with the corresponding interval to obtain a paired item;

[0110] Obtain a preset blank database, and add the paired item into the blank database;

[0111] After all the paired items to be added into the blank database are added, use the blank database as an interval-delay library to complete the construction.

[0112] The working principle and beneficial effects of the above technical solution are as follows:

[0113] When constructing an interval-delay library, a preset interval is introduced, and the interval is different estimated ranging intervals. Obtain multiple test records corresponding to the interval for performing interval-appropriate delay tests. The interval-appropriate test means that the tester fixes the millimeter-wave radar and the target object, the distance between the millimeter-wave radar and the target object is fixed, after estimating the ranging interval of the measurement area, different delay chirps are set, and according to the final ranging result and the fixed distance between the millimeter-wave radar and the target object, the rationality of the setting of the delay chirp is determined. The test records include the test process and the test result. The test process is, for example: which testers and what test operations the testers perform, etc. The test result is the appropriate delay chirp determined.

[0114] It is desired to determine the appropriate delay chirp corresponding to different intervals according to the test records. However, due to the large influence of human factors in the test, the test process needs to be verified. The test process is split into multiple sub-processes, and a preset first feature extraction template and a process evaluation library corresponding to the process type of the sub-process are introduced. The process type can be, for example: test operation type, etc. The process evaluation library stores the evaluation values corresponding to different process description factors. Based on the first feature extraction template, feature extraction is performed on the sub-processes to obtain multiple first feature values, such as: the experience level value of the tester and the number of steps of the operation performed, etc. Based on the first feature values, process description factors are constructed. The process description factors can be description vectors constructed based on the first feature values. Constructing vectors and description vectors based on data both belong to the category of existing technologies and will not be elaborated. Based on the process description factors and the process evaluation library, the evaluation values are determined. Obtain the process weight of the sub-process corresponding to the test process. The process weight represents the importance of the sub-process relative to the test process. Assign the process weight corresponding to the sub-process (the two are multiplied) to obtain the target value. Cumulatively calculate the target values associated with the test records to obtain the sum of the target values. The cumulative calculation formula is: is the sum of the target values, α i is the i-th target value associated with the test record, and n is the total number of target values associated with the test record. The larger the sum of the target values, the more standardized the test process, etc. Select the delay in the test result of the test record corresponding to the largest sum of the target values and pair it with the corresponding interval, and include it in the blank database for database construction. This ensures the accuracy of the construction of the interval-delay library and improves the convenience and applicability of querying the delay T corresponding to the estimated ranging interval based on this library later. d

[0115] An embodiment of the present invention provides a millimeter-wave high-precision ranging method based on precise chirp delay. The obtaining of multiple test records corresponding to the interval for performing interval-appropriate delay tests includes:

[0116] Obtain a preset artificial input library;

[0117] Determine the test record for interval appropriate delay test input by the first tester corresponding to the interval from the artificial input library;

[0118] And / or,

[0119] When multiple second testers start the interval appropriate delay test, construct an online meeting room and connect all the second testers to the online meeting room;

[0120] Obtain multiple first conversation records generated by the tester in the online meeting room;

[0121] Determine the test record based on the first conversation record.

[0122] The working principle and beneficial effects of the above technical solution are:

[0123] There are two ways to obtain the test record: First, it is manually input by the first tester, and the test records manually input by different first testers are all stored in the artificial input library; Second, when each second tester starts the test, enter the online meeting room, have a conversation in the online meeting room, and determine the test record based on the first conversation record.

[0124] The embodiment of the present invention provides a millimeter wave high-precision ranging method based on precise chirp delay. Determining the test record based on the first conversation record includes:

[0125] Extract the semantics of the first conversation record to obtain the first semantics;

[0126] Obtain the preset irrelevant semantics library, and match the first semantics with the second semantics in the irrelevant semantics;

[0127] If the match is successful, delete the first conversation record corresponding to the successfully matched first semantics;

[0128] When all the first conversation records to be deleted are deleted, use the remaining first conversation records as the second conversation records;

[0129] Establish a timeline;

[0130] Obtain the generation time points of the conversation records;

[0131] Based on the generation time points, set the second conversation records on the timeline correspondingly;

[0132] Obtain the preset test semantics library;

[0133] Match the first semantics corresponding to the second conversation records with the third semantics in the test semantics library;

[0134] If the match is successful, obtain the preset item to be recorded corresponding to the third semantics that matches successfully. At the same time, use a preset number of the second conversation records before and / or after the second conversation record corresponding to the first semantics that matches successfully on the time axis as the third conversation record;

[0135] Based on the third conversation record, determine whether the item to be recorded takes effect;

[0136] If so, use the corresponding item to be recorded as the target to be recorded;

[0137] Integrate each of the targets to be recorded to obtain a test record.

[0138] The working principle and beneficial effects of the above technical solution are as follows:

[0139] When determining a test record based on a first conversation record, first, introduce a preset irrelevant semantics library. A large number of irrelevant semantics are stored in the irrelevant semantics library, such as "What time is it now" and "How long has the test been going on", etc. Match the first semantics extracted from the first conversation record with the second semantics in the irrelevant semantics library. If the match is successful, eliminate the corresponding first conversation record. Eliminating irrelevant conversation content reduces the resources for determining the test record and improves the efficiency of determining the test record.

[0140] Set the uneliminated second conversation records on the time axis. Introduce a preset test semantics library. A large number of semantics related to the test topic are stored in the test semantics library, such as "What is the ranging result", etc. Match the first semantics corresponding to the second conversation record with the third semantics in the test semantics library. If the match is successful, it indicates that recording is required. Obtain the preset item to be recorded corresponding to the third semantics that matches successfully. For example, if the third semantics is "Ranging 10m", the item to be recorded is "The ranging result is 10m". However, this item to be recorded is not necessarily the result that needs to be recorded. For example, the second tester makes a slip of the tongue when reading the distance and then says "Oh no, it's 10.1m" later. Therefore, it is necessary to determine whether the item to be recorded needs to be recorded, that is, whether it takes effect, according to a preset number of the third conversation records before and / or after the second conversation record corresponding to the first semantics that matches successfully on the time axis. Use the item to be recorded that takes effect as the target to be recorded and integrate it to obtain a test record. Determining the test record through the chat conversation process of the tester eliminates the need for the user to input it manually, improving the convenience. It is especially suitable for test scenarios where there is a large amount of data that needs to be recorded. In addition, effectively verifying the item to be recorded improves the accuracy of determining the test record based on the chat record.

[0141] An embodiment of the present invention provides a millimeter-wave high-precision ranging method based on accurate chirp delay. Determining whether the item to be recorded takes effect based on the third conversation record includes:

[0142] Obtain a preset semantic understanding model;

[0143] Input the second conversation record and the third conversation record corresponding to the first semantics that match into the semantic understanding model to determine whether the item to be recorded takes effect;

[0144] And / or,

[0145] Obtain a preset second feature extraction template and an effect determination library corresponding to the first semantics that match when matching with the third semantics;

[0146] Based on the second feature extraction template, perform feature extraction on the positional relationship on the time axis of the first semantics corresponding to the third conversation record, the second conversation record corresponding to the first semantics that match, and the third conversation record, to obtain a plurality of second feature values;

[0147] Based on the second feature values, construct semantic description factors;

[0148] Based on the effect determination library and the semantic description factors, determine whether the item to be recorded takes effect.

[0149] The working principle and beneficial effects of the above technical solution are as follows:

[0150] When determining whether an item to be recorded takes effect based on the third conversation record, there are two methods: First, introduce a preset semantic understanding model. The semantic understanding model is an artificial intelligence model obtained by training a neural network model to convergence using a large amount of manual semantic understanding records and / or a large number of effective semantics (for example: no change after stating the test result) and invalid semantics (for example: change after stating the test result) in the testing process. The model training and the neural network model belong to the category of existing technologies and will not be elaborated here. Input the second conversation record and the fourth conversation record corresponding to the first semantics that match into the semantic understanding model to determine whether the item to be recorded takes effect; Second, introduce a preset second feature extraction template and an effect determination library corresponding to the first semantics that match when matching with the third semantics. The effect determination library stores the results of determining whether to take effect corresponding to different semantic description factors. Based on the second feature extraction template, perform feature extraction on the positional relationship on the time axis of the first semantics corresponding to the third conversation record, the second conversation record corresponding to the first semantics that match, and the third conversation record, to obtain second feature values. The second feature values can be: the number of negative words in the semantics and the number of conversation record intervals, etc. Based on the second feature values, construct semantic description factors, which are similar to the process description factors. Based on the effect determination library and the semantic description factors, determine whether the item to be recorded takes effect. This improves the comprehensiveness and accuracy of determining whether the item to be recorded takes effect, and at the same time, it is also more intelligent.

[0151] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A millimeter-wave high-precision ranging method based on accurate chirp delay, characterized in that, Including: Step 1: Obtain the echo signal received when the millimeter-wave radar measures the distance to the target object; Step 2: Based on the echo signal and a preset original chirp signal, construct a first intermediate-frequency signal; Step 3: Based on the first intermediate-frequency signal, determine the coarse-grained estimated ranging interval of the target object; Step 4: Determine the delay T based on the estimated ranging interval d ; Step 5: Based on the echo signal and the delayed chirp signal that is delayed by the delay T with respect to the original chirp signal, construct a second intermediate frequency signal; d ​ Step 6: Based on the second intermediate-frequency signal, determine the fine-grained target distance of the target object; Step 4: Determine the delay T based on the estimated ranging interval d , including: Construct an interval-delay library; Based on the interval-delay library, determine the delay T corresponding to the estimated ranging interval d ; The construction of the interval-delay library includes: Obtain a preset test interval set, where the test interval set includes: multiple intervals; Obtain multiple test records for performing interval-appropriate delay tests corresponding to the intervals, where the test records include: test procedures and test results; Split the test procedure into multiple sub-procedures; Obtain a preset first feature extraction template and a process evaluation library corresponding to the process type of the sub-procedure; Based on the first feature extraction template, extract features from the sub-procedure to obtain multiple first feature values; Based on the first feature values, construct a process description factor; Based on the process evaluation library and the process description factor, determine the evaluation value; Obtain the process weight of the sub-procedure corresponding to the test procedure; Assign the evaluation value the corresponding process weight to obtain a target value, and associate it with the corresponding test record; Accumulatively calculate the target values associated with the test records to obtain the sum of the target values; Extract the delay in the test result of the test record corresponding to the maximum sum of the target values; Pair the delay with the corresponding interval to obtain a paired item; Obtain a preset blank database, and add the paired item into the blank database; After all the paired items to be added into the blank database are added, use the blank database as the interval-delay library to complete the construction.

2. The millimeter-wave high-precision ranging method based on accurate chirp delay according to claim 1, characterized in that, The Step 2: Based on the echo signal and a preset original chirp signal, construct a first intermediate-frequency signal, includes: Based on a preset first construction rule, according to the echo signal and the preset original chirp signal, construct a first intermediate-frequency signal.

3. The millimeter-wave high-precision ranging method based on accurate chirp delay according to claim 1, characterized in that, The Step 3: Based on the first intermediate-frequency signal, determine the coarse-grained estimated ranging interval of the target object, includes: Based on a preset first analysis rule, analyze the first intermediate-frequency signal to obtain multiple first distance values; Use the maximum and minimum values among the first distance values as the interval boundaries respectively to make the coarse-grained estimated ranging interval of the target object.

4. The millimeter-wave high-precision ranging method based on accurate chirp delay according to claim 1, characterized in that, Step 5: Based on the echo signal and the delayed chirp signal that is delayed by the delay T with respect to the original chirp signal, construct a second intermediate frequency signal, including: d After the delay, the chirp signal constructs a second intermediate frequency signal, including: Based on a preset second construction rule, a second intermediate frequency signal is constructed according to the echo signal and the delayed chirp signal that is delayed by the delay T relative to the original chirp signal. d After that, the delayed chirp signal is used to construct the second intermediate frequency signal.

5. A millimeter-wave high-precision ranging method based on precise chirp delay as described in claim 1, characterized in that, The determination of the fine-grained target distance of the target object based on the second intermediate-frequency signal includes: Based on a preset second analysis rule, analyze the second intermediate-frequency signal to obtain multiple second distance values, and use them as the fine-grained target distance of the target object.

6. A millimeter-wave high-precision ranging method based on precise chirp delay as described in claim 1, characterized in that, The obtaining of multiple test records for performing interval-appropriate delay tests corresponding to the intervals includes: Obtain a preset manual input library; Determine the test records for performing interval-appropriate delay tests input by the first tester corresponding to the interval from the manual input library; And / or When multiple second testers start the interval appropriate delay test, an online meeting room is constructed and all the second testers are connected to the online meeting room; Obtain multiple first conversation records generated by the second testers in the online meeting room; Based on the first conversation records, determine test records.

7. A millimeter-wave high-precision ranging method based on precise chirp delay as described in claim 6, characterized in that, The determining the test records based on the first conversation records includes: Perform semantic extraction on the first conversation records to obtain first semantics; Obtain a preset irrelevant semantic library and match the first semantics with second semantics in the irrelevant semantics; If the match is successful, delete the first conversation records corresponding to the first semantics that match successfully; When all the first conversation records to be deleted have been deleted, use the remaining first conversation records as second conversation records; Establish a timeline; Obtain the generation time points of the conversation records; Based on the generation time points, set the second conversation records correspondingly on the timeline; Obtain a preset test semantic library; Match the first semantics corresponding to the second conversation records with third semantics in the test semantic library; If the match is successful, obtain preset items to be recorded corresponding to the third semantics that match successfully. At the same time, use the second conversation records before and / or after the second conversation records corresponding to the first semantics that match successfully on the timeline as third conversation records; Based on the third conversation records, determine whether the items to be recorded are effective; If so, use the corresponding items to be recorded as targets to be recorded; Integrate all the targets to be recorded to obtain test records.

8. A millimeter-wave high-precision ranging method based on precise chirp delay as described in claim 7, characterized in that, The determining whether the items to be recorded are effective based on the third conversation records includes: Obtain a preset semantic understanding model; Input the second conversation records corresponding to the first semantics that match successfully and the third conversation records into the semantic understanding model to determine whether the items to be recorded are effective; And / or, Obtain a preset second feature extraction template and an effectiveness determination library corresponding to the first semantics that match successfully when matching with the third semantics; Based on the second feature extraction template, perform feature extraction on the position relationship between the first semantics corresponding to the third conversation records, the second conversation records corresponding to the first semantics that match successfully, and the third conversation records on the timeline to obtain multiple second feature values; Based on the second feature values, construct a semantic description factor; Based on the effectiveness determination library and the semantic description factor, determine whether the items to be recorded are effective.

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