A radar high-altitude target recognition method, system and device based on multi-path interference fringe feature solution

Abstract

This invention relates to the field of vehicle-mounted radar technology, and discloses a radar high-altitude target identification method, system, and device based on multipath interference fringe feature calculation. The key technical points include the following steps: Based on the principle of vehicle radar, a multipath interference geometric model is constructed; in response to an identification trigger command, the vehicle's pitch angle is acquired, and an amplitude-range evolution sequence is constructed; amplitude smoothing is performed, and based on the vehicle's pitch angle and the multipath interference geometric model, frequency clutter outside the corresponding frequency range under normal radar operating conditions is calculated and filtered out to obtain target interference fringes; the dominant frequency or the spacing between adjacent peaks is extracted from the target interference fringes; the height of the target is obtained through reverse calculation; the confidence level of the target height is evaluated using a confidence index; if the confidence index exceeds a preset threshold, the target type corresponding to the target height is identified using a preset target classification standard.

Description

Technical Field

[0001] This invention relates to the field of vehicle-mounted radar technology, and more specifically, to a radar high-altitude target identification method, system, and device based on multipath interference fringe feature calculation. Background Technology

[0002] Vehicle-mounted millimeter-wave radar plays a crucial role in autonomous driving perception. When identifying stationary targets ahead, it is essential to distinguish between high-altitude targets and stationary ground targets. High-altitude targets include suspended road signs, traffic lights, etc., which vehicles can safely pass through; stationary ground targets include disabled vehicles, scattered objects, etc., which vehicles must avoid.

[0003] Existing identification methods mainly rely on adding an elevation antenna channel (MIMO technology) to directly measure the elevation angle, or on using the ratio of sidelobes to main lobes for judgment. However, existing technologies have the following drawbacks:

[0004] Physical limitations: Ordinary vehicle-mounted radars have small vertical apertures and low pitch resolution, typically greater than 2°. At long distances, such as greater than 100 meters, even small angle measurement errors can lead to huge deviations in altitude calculations.

[0005] Multipath interference misjudgment: Traditional angle measurement algorithms regard "ground multipath reflections" as interference signals and attempt to suppress them through filtering. However, in actual roads, ground reflection signals are strong and have complex phases, often causing angle measurement results to fluctuate wildly between positive and negative, making the judgment based on angle thresholds ineffective.

[0006] Single amplitude characteristics: Existing technologies only utilize the absolute value or growth trend of amplitude, ignoring the subtle fluctuation characteristics of amplitude as it changes with distance, i.e., physical interference patterns. Summary of the Invention

[0007] The purpose of this invention is to provide a radar high-altitude target identification method, system, and device based on multipath interference fringe feature calculation. Instead of attempting to suppress multipath effects, it utilizes the interference fringes generated by the superposition of direct radar waves and ground-reflected waves. By combining vehicle dynamics data with dynamic compensation of the geometric model, and based on the principle that the echo amplitude of targets at different altitudes will oscillate and fade at different frequencies during vehicle approach, the physical altitude of the target can be accurately calculated from a long distance by analyzing the "spatial frequency" of the echo amplitude variation with distance.

[0008] The above-mentioned technical objective of the present invention is achieved through the following technical solution: a radar high-altitude target identification method based on multipath interference fringe feature calculation, comprising the following steps:

[0009] S1. Based on the principle of vehicle radar, a multipath interferometric geometric model is constructed to determine the correlation between the height of the target being measured, the distance between the vehicle and the target being measured, the radar wavelength, the vehicle body pitch angle, and the radar echo amplitude.

[0010] S2. In response to the identification trigger command, the vehicle pitch angle is collected, and the distance between the vehicle and the target and the radar echo amplitude data pairs of the target in multiple consecutive frames are recorded to construct an amplitude-distance evolution sequence.

[0011] S3. Perform amplitude smoothing on the amplitude-range evolution sequence. Based on the vehicle pitch angle and multipath interference geometry model, calculate and filter out frequency clutter outside the corresponding frequency range under normal radar operation to obtain target interference fringes.

[0012] S4. Extract the dominant frequency or the spacing between adjacent peaks from the target interference fringes;

[0013] S5. The height of the target under test is obtained by inverse calculation using the main frequency or the spacing between adjacent wave peaks and the multipath interference geometric model.

[0014] S6. Evaluate the credibility of the height of the target under test through the confidence index. If the confidence index exceeds the preset threshold, identify the type of target under test corresponding to the height of the target under test through the preset target classification standard.

[0015] As a preferred embodiment of the present invention, the multipath interference geometric model includes:

[0016] Let the height of the target be H, the radar wavelength be λ, and the radar installation height be denoted as H. The distance from the front axle is denoted as L. When the vehicle is moving, it produces a pitch angle. At that time, the radar's real-time ground altitude Recorded as: ;

[0017] When the distance between the vehicle and the target is R, the difference between the direct path and the ground reflection path Recorded as:

[0018] ;

[0019] The received signal is the superposition of the signals from the two direct paths and the signal from the ground reflection path. Assuming the ground reflection coefficient is approximately 1, the amplitudes of the received signals from the direct path and the ground reflection path are equal. According to the two-wave interference amplitude formula, the amplitude of the received signal is: ;

[0020] Will Substituting the values, we obtain the relationship between the received signal amplitude A and the distance R:

[0021] That is, the amplitude A of the received signal exhibits cosine oscillation as the distance R changes.

[0022] As a preferred technical solution of the present invention, in S3, the amplitude smoothing process performed on the amplitude-distance evolution sequence includes moving average processing, which is used to remove amplitude instability caused by random flickering of the target RCS and other random fluctuations, and retain the periodic fluctuation component caused by interference.

[0023] As a preferred technical solution of the present invention, in S3, the vehicle body pitch angle is considered. Estimate the theoretical interference frequency window within the expected target height range;

[0024] According to the multipath interference geometric model, the spatial frequency of the interference fringes is denoted as: ;

[0025] We can obtain: spatial frequency and Proportional to, with Inversely proportional;

[0026] Based on the set target height H corresponding to normal radar operation and the radar's real-time ground altitude... The distance R between the vehicle and the target is used to calculate the corresponding frequency range under normal radar operating conditions.

[0027] By using a bandpass filter, frequency clutter outside the frequency range corresponding to the normal operating conditions of the radar is filtered out.

[0028] As a preferred embodiment of the present invention, in S4, the dominant frequency or the spacing between adjacent peaks is extracted by peak-valley counting or short-time Fourier transform. .

[0029] As a preferred embodiment of the present invention, in step S5, the height of the target being measured is calculated as follows:

[0030] Let the distances between two adjacent wave crests be R1 and R2, then the distance difference between the wave crests is: , The target height H can be estimated using the following formula: .

[0031] As a preferred embodiment of the present invention, in S6, the confidence index CS is calculated as follows:

[0032] Given the target height H and radar height All positions between R1 and R2 An ideal signal can be constructed based on the formula for the amplitude of two-wave interference: ;

[0033] Calculate the confidence index CS using the Pearson correlation coefficient:

[0034] ;

[0035] in for The mean, for The mean, For all locations The measured amplitude sequence.

[0036] A radar high-altitude target identification system based on multipath interferometric fringe feature calculation includes:

[0037] The model building module is used to construct a multipath interferometric geometric model based on the vehicle radar principle, and to determine the correlation between: the height of the target being measured, the distance between the vehicle and the target being measured, the radar wavelength, the vehicle body pitch angle, and the radar echo amplitude.

[0038] Data acquisition module: used to respond to identification trigger commands, acquire vehicle pitch angle, and record the distance between the vehicle and the target and radar echo amplitude data pairs in multiple consecutive frames;

[0039] Data preprocessing module: used to construct amplitude-range evolution sequence, perform amplitude smoothing on amplitude-range evolution sequence, calculate and filter out frequency clutter outside the frequency range corresponding to the normal radar operating conditions based on vehicle pitch angle and multipath interference geometry model, and obtain target interference fringes;

[0040] Feature extraction and quality assessment module: Extracts the dominant frequency or the spacing between adjacent peaks of the target interference fringes and calculates the confidence index;

[0041] Height calculation module: The height of the target under test is obtained by inverse calculation using the peak spacing and multipath interference geometric model;

[0042] Target Classification and Decision Module: Based on the calculated height of the target being measured, the module identifies the type of target being measured using preset target classification criteria.

[0043] A radar high-altitude target identification device based on multipath interference fringe feature calculation includes: a processor and a memory, wherein the memory stores a computer program executable by the processor, and the processor implements the above-mentioned method when executing the computer program.

[0044] In summary, the present invention has the following beneficial effects:

[0045] Overcoming hardware limitations, even radars without elevation angle measurement capabilities, such as radars with only horizontal channels, can still identify altitude through amplitude changes.

[0046] It has strong anti-interference capabilities, utilizing the wave period of the signal rather than its absolute intensity, and is less affected by the size of the target's radar cross section.

[0047] It is more accurate at long distances. The further the distance, the more obvious the multipath effect and the more stable the interference characteristics, which makes up for the shortcoming of traditional angle measurement at long distances. Attached Figure Description

[0048] Figure 1 This is a flowchart of the method of the present invention;

[0049] Figure 2 This is a schematic diagram of the physical principle of multipath interference in this invention;

[0050] Figure 3 This is a comparison diagram of the amplitude characteristics of high-altitude targets and ground targets according to the present invention;

[0051] Figure 4 This is a theoretical interference fringe diagram illustrating how the amplitude of radar echoes from high-altitude targets varies with distance. Detailed Implementation

[0052] It is readily understood that, based on the technical solutions of this invention, various embodiments of the invention can be conceived by those skilled in the art without altering the essential spirit of the invention. Therefore, the following detailed embodiments and accompanying drawings are merely illustrative examples of the technical solutions of this invention and should not be considered as the entirety of the invention or as limitations or restrictions on the technical solutions of this invention. Rather, the purpose of providing these embodiments is to enable those skilled in the art to more thoroughly understand the invention. Preferred embodiments of the invention are described below in conjunction with the accompanying drawings, which form part of this application and, together with the embodiments of the invention, serve to illustrate the innovative concept of the invention.

[0053] like Figure 1 As shown, this invention provides a radar high-altitude target identification method based on multipath interference fringe feature calculation, comprising the following steps:

[0054] S1. Based on the principle of vehicle radar, construct a multipath interferometric geometric model to determine: the height H of the target, the distance R between the vehicle and the target, the radar wavelength λ, and the radar installation height. Vehicle pitch angle The correlation between the radar distance from the front axle L, the difference between the direct path and the ground reflection path Δr, and the radar echo amplitude A;

[0055] Specifically, multipath interference geometric models include:

[0056] like Figure 2 As shown, the height of the target to be measured is denoted as H, the radar wavelength as λ, and the radar installation height as [missing information]. The distance from the front axle is denoted as L. When the vehicle is moving, it produces a pitch angle. At that time, the radar's real-time ground altitude Recorded as: ;

[0057] When the distance between the vehicle and the target is R, the difference between the direct path and the ground reflection path Recorded as:

[0058] ;

[0059] The received signal is the superposition of the signals from the two direct paths and the signal from the ground reflection path. Assuming the ground reflection coefficient is approximately 1, the amplitudes of the received signals from the direct path and the ground reflection path are equal. According to the two-wave interference amplitude formula, the amplitude of the received signal is: ;

[0060] Will Substituting the values, we obtain the relationship between the received signal amplitude A and the distance R:

[0061] ;

[0062] The relationship shows that the received signal amplitude A exhibits cosine oscillations as the distance R changes. The oscillation frequency is not only proportional to the target height H, but also influenced by the real-time radar altitude. Modulation.

[0063] S2. In response to the recognition trigger command, record the data pairs of vehicle-to-target distance R and echo amplitude A in multiple consecutive frames to construct an amplitude-distance evolution sequence.

[0064] The identification trigger command is mainly determined based on vehicle speed. Too low a speed results in an excessively long observation window, while too high a speed results in too few samples. Here, the vehicle speed range is limited to 10-120 km / h based on the usage scenario. The target to be measured is usually set as a static target in front of the vehicle that may affect traffic, such as static targets in the same lane and adjacent lanes: ±6m laterally and 20-250m ahead.

[0065] In this step, in response to the identified trigger command, the vehicle pitch angle is also collected simultaneously. The specific operation involves reading the vehicle chassis CAN data, including vehicle speed, pitch angle, suspension height, and other relevant data.

[0066] S3, such as Figure 4 As shown, amplitude smoothing is performed on the amplitude-range evolution sequence, and frequency clutter outside the corresponding frequency range under normal radar operation is calculated and filtered out according to the multipath interferometry model to obtain the target interferometric fringes.

[0067] S3 is used for interference feature extraction, frequency domain analysis of amplitude sequences, or peak and trough detection. For example... Figure 3 As shown, high-altitude targets exhibit high-frequency periodic oscillations in amplitude and dense interference fringes due to rapid changes in path difference; while ground targets exhibit monotonically increasing amplitude or extremely low-frequency fluctuations due to extremely slow changes in path difference.

[0068] In S3, amplitude smoothing processing of the amplitude-distance evolution sequence, including moving average processing, is performed to remove amplitude instability caused by random flickering of the target RCS and other random fluctuations, while retaining the periodic fluctuation components caused by interference.

[0069] In the S3, the vehicle's pitch angle is also taken into account. Based on the expected target height range, estimate the theoretical interference frequency window.

[0070] According to the multipath interference geometric model, the spatial frequency of the interference fringes is denoted as:

[0071] ;

[0072] We can obtain: spatial frequency and Proportional to, with Inversely proportional; therefore, based on the set target height H corresponding to the normal radar operating conditions and the radar's real-time ground altitude... The distance R between the vehicle and the target is used to calculate the corresponding frequency range under normal radar operating conditions. For example, under normal radar operating conditions, the height of the target H ∈ [2m, 8m], the distance R between the vehicle and the target R ∈ [20m, 250m], and the real-time ground altitude of the radar is... ∈[0.3m, 0.6m], the theoretical frequency window range is .

[0073] By using a bandpass filter, frequency clutter outside the frequency range corresponding to the normal operating conditions of the radar is filtered out.

[0074] S4. Extract the dominant frequency or the spacing between adjacent peaks from the target interference fringes. The dominant frequency or the spacing between adjacent peaks can be extracted using peak-valley counting or short-time Fourier transform methods. .

[0075] S5, via the peak spacing The height of the target under test is obtained by inverse calculation using the multipath interference geometric model;

[0076] The height of the target being measured is calculated as follows: Let the distance between two adjacent wave crests be R1 and R2, then the distance difference between the wave crests is... The peak spacing is the reciprocal of the spatial frequency, and the received signal amplitude A(R) is the actual signal.

[0077] |cos(·)|, the absolute value operation will double the signal frequency, so the relationship between spatial frequency and peak spacing is: If the calculation is of frequency, it is also converted to .

[0078] The target height H can be estimated using the following formula: ;

[0079] S6. Introduce the confidence index CS to evaluate the reliability of the altitude calculation. Given the estimated altitude H and the radar altitude... All positions between R1 and R2 An ideal signal can be constructed based on the aforementioned formula for the amplitude of two-wave interference:

[0080] ;

[0081] Calculate the confidence index CS using the Pearson correlation coefficient:

[0082] ;

[0083] in for The mean, for The mean, For all locations The measured amplitude sequence.

[0084] If CS is less than the preset value, then output Target_Type=Unknown; and mark the target as "highly untrustworthy".

[0085] If the confidence index exceeds a preset threshold, the target type is identified based on the calculated target height and a preset target classification standard. For example, if the calculated height is greater than 5m, it is considered a high-altitude target, and the target is deemed traversable to avoid false triggering of the Automatic Emergency Braking (AEB) system. If the height is less than 1.5m and the confidence index is higher than a set threshold (e.g., 0.8), it is considered a ground obstacle. Other cases are classified as uncertain targets.

[0086] The following is an example of a system logic judgment in S6:

[0087] Set H thr CS is the threshold for determining the altitude of high-altitude targets. thr Set the corresponding confidence index threshold; set H thr2 CS is the threshold for determining the height of ground targets. thr2 The corresponding confidence index threshold;

[0088] IF(H>Hthr AND(CS>CS) thr ):

[0089] It has been identified as a high-altitude target.

[0090] Strategy: Suppress AEB (Automatic Emergency Braking) triggering and allow vehicles to pass.

[0091] ELSEIF((H <H thr2 AND(CS>CS) thr2 )):

[0092] It has been identified as a ground target.

[0093] Strategy: Issue collision warnings as normal.

[0094] ELSE:

[0095] The target is classified as "uncertain." Maintain the current tracking status and refrain from making hasty decisions.

[0096] In one embodiment, the multipath interferometric geometry model also defines the correlation between the vehicle suspension height and the actual radar height. In S2, the vehicle suspension height is also acquired synchronously, and in S3, the actual radar height is calculated based on the vehicle suspension height and the correlation between the two.

[0097] Corresponding to the above method, the present invention also provides a radar high-altitude target identification system based on multipath interferometric fringe feature calculation, comprising:

[0098] The model building module is used to construct a multipath interferometric geometric model based on the vehicle radar principle, and to determine the correlation between: the height of the target being measured, the distance between the vehicle and the target being measured, the radar wavelength, the vehicle body pitch angle, and the radar echo amplitude.

[0099] Data acquisition module: used to respond to recognition trigger commands and record data pairs of distance R between the vehicle and the target and echo amplitude A within multiple consecutive frames;

[0100] Data preprocessing module: used to construct amplitude-range evolution sequence, perform amplitude smoothing on amplitude-range evolution sequence, and calculate and filter out frequency clutter outside the corresponding frequency range under normal radar operation based on multipath interferometry model to obtain target interferometric fringes;

[0101] Feature extraction and quality assessment module: Extracts the dominant frequency or the spacing between adjacent peaks from the target interference fringes. And calculate the confidence index;

[0102] Height calculation module: based on peak spacing The height of the target under test is obtained by inverse calculation using the multipath interference geometric model;

[0103] Target Classification and Decision Module: Based on the calculated height of the target, the module identifies the target type using preset target classification criteria. It also helps in formulating corresponding strategies. For example, if the target is identified as a high-altitude target, a decision is made that it can be traversed; for instance, if CS in S4 is less than a preset value, the current result is unreliable, and a conservative strategy is adopted, such as prompting a reduction in speed or continuing tracking.

[0104] Corresponding to the above methods and systems, the present invention also provides a radar high-altitude target identification device based on multipath interference fringe feature calculation, comprising: a processor and a memory, wherein the memory stores a computer program executable by the processor, and the processor implements the methods described in S1-S6 when executing the computer program.

[0105] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto.

[0106] Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this invention should be included within the protection scope of this invention.

[0107] It should be understood that, in order to simplify the present invention and help those skilled in the art understand its various aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes described in a single embodiment or with reference to a single figure. However, the present invention should not be construed as implying that all features included in the exemplary embodiments are essential technical features of the claims of the present invention.

[0108] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0109] It should be understood that the modules, units, components, etc., included in the device of one embodiment of the present invention can be adaptively changed to be placed in a device different from that embodiment. Different modules, units, or components included in the device of the embodiment can be combined into a single module, unit, or component, or they can be divided into multiple sub-modules, sub-units, or sub-components.

[0110] The modules, units, or components in the embodiments of the present invention can be implemented in hardware, in software running on one or more processors, or in a combination thereof. Those skilled in the art should understand that...

[0111] In practice, microprocessors or digital signal processors (DSPs) can be used to implement embodiments of the invention. The invention can also be implemented on computer program products or computer-readable media for performing some or all of the methods described herein.

Claims

1. A radar high-altitude target identification method based on multipath interference fringe feature calculation, characterized by: Includes the following steps: S1. Based on the principle of vehicle radar, a multipath interferometric geometric model is constructed to determine the correlation between: the height of the target, the distance between the vehicle and the target, the radar wavelength, the vehicle's pitch angle, and the radar echo amplitude; the multipath interferometric geometric model includes: the height of the target denoted as H, the radar wavelength denoted as λ, and the radar installation height denoted as... The distance from the front axle is denoted as L. When the vehicle is moving, it produces a pitch angle. At that time, the radar's real-time ground altitude Recorded as: When the distance between the vehicle and the target is R, the difference between the direct path and the ground reflection path is... Recorded as: The received signal is the superposition of the signals from the two direct paths and the signal from the ground reflection path. Assuming the ground reflection coefficient is approximately 1, the amplitudes of the received signals from the direct path and the ground reflection path are equal. According to the two-wave interference amplitude formula, the amplitude of the received signal is: ;Will Substituting the values, we obtain the relationship between the received signal amplitude A and the distance R: That is, the amplitude A of the received signal exhibits a cosine oscillation as the distance R changes; S2. In response to the identification trigger command, the vehicle pitch angle is collected, and the distance between the vehicle and the target and the radar echo amplitude data pairs of the target in multiple consecutive frames are recorded to construct an amplitude-distance evolution sequence. S3. Perform amplitude smoothing on the amplitude-range evolution sequence. Based on the vehicle pitch angle and multipath interference geometry model, calculate and filter out frequency clutter outside the corresponding frequency range under normal radar operation to obtain target interference fringes. S4. Extract the dominant frequency or the spacing between adjacent peaks from the target interference fringes; S5. The height of the target under test is obtained by reverse calculation using the main frequency or the spacing between adjacent wave peaks and the multipath interference geometric model. S6. Evaluate the credibility of the height of the target under test through the confidence index. If the confidence index exceeds the preset threshold, identify the type of target under test corresponding to the height of the target under test through the preset target classification standard.

2. The radar high-altitude target identification method based on multipath interference fringe feature calculation according to claim 1, characterized in that: S3 In the amplitude-distance evolution sequence, amplitude smoothing processing, including moving average processing, is performed to remove amplitude instability caused by random flickering of the target RCS and other random fluctuations, while retaining the periodic fluctuation components caused by interference.

3. The radar high-altitude target identification method based on multipath interference fringe feature calculation according to claim 2, characterized in that: in S3, the vehicle pitch angle is combined with... Estimate the theoretical interference frequency window within the expected target height range; According to the multipath interference geometric model, the spatial frequency of the interference fringes is denoted as: ; We can obtain: spatial frequency and Proportional to, with Inversely proportional; Based on the set target height H corresponding to normal radar operation and the radar's real-time ground altitude... The distance R between the vehicle and the target is used to calculate the corresponding frequency range under normal radar operating conditions. By using a bandpass filter, frequency clutter outside the frequency range corresponding to the normal operating conditions of the radar is filtered out.

4. The radar high-altitude target identification method based on multipath interference fringe feature calculation according to claim 3, characterized in that: In S4, the dominant frequency or the spacing between adjacent peaks is extracted using the peak-valley counting method or the short-time Fourier transform method. .

5. The radar high-altitude target identification method based on multipath interference fringe feature calculation according to claim 1, characterized in that: S5 In this context, the height of the target being measured is calculated as follows: Let the distances between two adjacent wave crests be R1 and R2, then the distance difference between the wave crests is: , The target height H can be estimated using the following formula: .

6. The radar high-altitude target identification method based on multipath interference fringe feature calculation according to claim 5, characterized in that: in S6, the confidence index CS is calculated as follows: Given the target height H and the radar height All positions between R1 and R2 An ideal signal can be constructed based on the formula for the amplitude of two-wave interference: ; Calculate the confidence index CS using the Pearson correlation coefficient: ； in for The mean, for The mean, For all locations The measured amplitude sequence.

7. A radar high-altitude target identification system based on multipath interferometric fringe feature calculation, characterized in that: include: The model building module is used to construct a multipath interferometric geometry model based on the principles of vehicle radar, determining the correlation between: the height of the target, the distance between the vehicle and the target, the radar wavelength, the vehicle's pitch angle, and the radar echo amplitude. The multipath interferometric geometry model includes: the target height denoted as H, the radar wavelength as λ, and the radar installation height as... The distance from the front axle is denoted as L. When the vehicle is moving, it produces a pitch angle. At that time, the radar's real-time ground altitude Recorded as: When the distance between the vehicle and the target is R, the difference between the direct path and the ground reflection path is... Recorded as: The received signal is the superposition of the signals from the two direct paths and the signal from the ground reflection path. Assuming the ground reflection coefficient is approximately 1, the amplitudes of the received signals from the direct path and the ground reflection path are equal. According to the two-wave interference amplitude formula, the amplitude of the received signal is: ;Will Substituting the values, we obtain the relationship between the received signal amplitude A and the distance R: That is, the amplitude A of the received signal exhibits a cosine oscillation as the distance R changes; Data acquisition module: used to respond to identification trigger commands, acquire vehicle pitch angle, and record the distance between the vehicle and the target and radar echo amplitude data pairs in multiple consecutive frames; Data preprocessing module: used to construct amplitude-range evolution sequence, perform amplitude smoothing on amplitude-range evolution sequence, calculate and filter out frequency clutter outside the frequency range corresponding to the normal radar operating conditions based on vehicle pitch angle and multipath interference geometry model, and obtain target interference fringes; Feature extraction and quality assessment module: Extracts the dominant frequency or the spacing between adjacent peaks of the target interference fringes and calculates the confidence index; Height calculation module: The height of the target under test is obtained by inverse calculation using the peak spacing and multipath interference geometric model; Target Classification and Decision Module: Based on the calculated height of the target being measured, the module identifies the type of target being measured using preset target classification criteria.

8. A radar high-altitude target identification device based on multipath interferometric fringe feature calculation, characterized in that: include: A processor and a memory, the memory storing a computer program executable by the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-6.

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