Multi-signal classification height measurement method based on meter-wave multiple-input-multiple-output radar

Abstract

The invention provides a multi-signal classification height measurement method based on a meter-wave multiple-input-multiple-output radar, and belongs to the technical field of radar signal processing, and the method comprises the steps: carrying out the modeling of a received signal, and carrying out the calculation to obtain an output signal; array data covariance is calculated to obtain a noise subspace, an initial value of a direct wave is obtained by using a generalized multiple signal classification method, and an initial value of a horizontal polarized wave reflection coefficient is obtained by using multiple signal classification; alternately searching according to the sequence of the estimated direct wave estimated angle initial value and the estimated horizontal polarized wave reflection estimated coefficient initial value to obtain an estimated parameter group; judging the estimation parameter group, if a judgment condition is met, outputting a direct wave estimation angle, otherwise, returning to carry out alternate search; and the target height is calculated by using the direct wave estimation angle, and multi-signal classification height measurement is completed. According to the method, the problems that redundant spectrum peaks are generated by an existing steering vector synthesis algorithm, and the calculation amount is sharply increased due to dense grid division search are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a multi-signal classification height measurement method based on a meter-wave multi-input multi-output radar. Background Art

[0002] Early meter-wave radars were widely used in the field of long-range target early warning due to their advantages of low propagation attenuation, long detection distance and simple implementation. However, the longer wavelength of meter-wave radars also led to a decrease in resolution, making it impossible to use meter-wave radars in tasks such as tracking and guidance. In modern warfare, emerging stealth technologies have directly driven the development of anti-stealth technology. With its natural advantages in anti-stealth and anti-radiation missiles, meter-wave radars have once again become a research hotspot. However, when meter-wave radars detect low-altitude targets, the longer electromagnetic wavelength brings a very wide beam, resulting in serious multipath effects, which in turn cause problems such as lobe splitting. Among them, the multipath signal and the direct wave signal are coherent, making some subspace direction of arrival (DOA) estimation algorithms unavailable. Low-elevation-angle height measurement (equivalent to DOA estimation) of meter-wave radars has become a problem that needs to be solved in the radar field.

[0003] Multiple-input multiple-output (MIMO) radar is a new system radar that has been widely studied in recent years. Different from traditional array radar, its unique waveform diversity capability makes it have the advantages of strong anti-interception and anti-interference capabilities and multiple virtual array elements. Applying the MIMO system to the meter-wave radar can narrow the receiving virtual beam and effectively alleviate the influence of the multipath effect. However, in the meter-wave MIMO radar, due to the influence of the transmitted orthogonal waveform, the virtual steering vectors penetrate each other, resulting in the inability to directly apply the traditional decorrelation algorithm, and thus making the MUSIC algorithm unable to be applied to the height measurement of the meter-wave MIMO radar. The prior art derives the application of the generalized MUSIC algorithm in the meter-wave MIMO radar, and the algorithm does not need to perform decorrelation processing. The prior art uses the dimensionality reduction method to reduce the amount of calculation, but it requires certain prior knowledge. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a multiple signal classification height measurement method based on a meter-wave multi-input multi-output radar, which solves the problem of redundant spectral peaks generated by the existing guidance vector synthesis algorithm and a sharp increase in the amount of calculation caused by dense grid division search.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is: a multi-signal classification height measurement method based on meter-wave multi-input multi-output radar, comprising the following steps: S1. Model the multipath receiving signal of the meter-wave multi-input multi-output radar according to the antenna array and the height measurement target, perform matched filtering and vectorization on the received multi-input multi-output array receiving signal, and calculate the output signal; S2. Calculate the array data covariance according to the output signal and combine them into a covariance matrix, obtain the noise subspace according to the covariance matrix, use the generalized multiple signal classification method to obtain the initial value of the direct wave, and use the multiple signal classification to obtain the initial value of the horizontal polarization wave reflection coefficient; S3, according to the generalized multiple signal classification method and the multiple signal classification method, an alternate search is performed in the order of estimating the initial value of the direct wave estimation angle and estimating the initial value of the horizontal polarization wave reflection estimation coefficient in S2 to obtain an estimation parameter group including the direct wave estimation angle and the horizontal polarization wave reflection estimation coefficient; S4, define the accuracy threshold and iteration threshold, and judge the estimated parameter group. If the accuracy of the estimated parameter group is less than the accuracy threshold or the number of iterations of the estimated parameter group is greater than the iteration threshold, output the direct wave estimation angle, otherwise return to step S3; S5. Use the direct wave to estimate the angle, and combine the projection distance between the antenna array and the height measurement target in the multi-path receiving signal model of the meter-wave multi-input multi-output radar and the height of the antenna array to calculate the target height and complete the multi-signal classification height measurement.

[0006] The beneficial effects of the present invention are as follows: the present invention obtains a relatively ideal signal model by modeling the multipath received signal of the meter-wave multi-input multi-output radar, and avoids the sharp increase in the amount of calculation caused by dense grid division search through generalized multiple signal classification and multiple signal classification alternating search, thereby achieving a good low-elevation angle height measurement effect, and the method of the present invention does not need to be decohered, and has a high engineering practical value.

[0007] Furthermore, the S1 comprises the following steps: S101, modeling the multipath receiving signal of the meter-wave multi-input multi-output radar according to the antenna array and the height measurement target; S102, obtaining a signal of the height measurement target being illuminated by the radar according to a transmission signal steering vector and a multipath steering vector of the transmission signal in a multi-path receiving signal model of a meter-wave multi-input multi-output radar; S103, obtaining an echo signal of a corresponding array element according to a signal of the height measurement target being illuminated by the radar and an array element of the antenna array, and obtaining a multi-input multi-output array receiving signal using the echo signal of each array element; S104, performing matched filtering and vectorization on the signals received by the multi-input multi-output array, and calculating and obtaining the output signals.

[0008] The beneficial effects of the above further scheme are as follows: the present invention improves the accuracy of using the corresponding data in the model by modeling the multi-path received signal of the meter-wave multi-input multi-output radar, and uses the array elements in the antenna array to accurately receive the echo signal, and obtains the output signal by matching filtering and vectorizing the received signal of the multi-input multi-output array. Considering the noise, the noise output by the matched filter is realized as Gaussian white noise.

[0009] Furthermore, the S2 comprises the following steps: S201, calculating array data covariance according to the output signal, combining the array data covariance into a covariance matrix, and performing eigendecomposition on the covariance matrix to obtain a noise subspace; S202, obtaining an initial value of the direct wave estimation angle using a generalized multiple signal classification method according to the noise subspace; S203, according to the multipath receiving signal model of the meter-wave multi-input multi-output radar, using the horizontal polarization wave reflection coefficient and the direct wave angle, calculating the steering vector of the received data, and according to multiple signal classification, using the steering vector of the received data and the noise subspace, obtaining the initial value of the horizontal polarization wave reflection estimation coefficient.

[0010] Furthermore, the expression of the multiple signal classification is as follows: ; ; ; in, represents the search space spectrum value of the direct wave angle and reflection coefficient, represents the steering vector of the received data, represents the direct wave angle, represents the horizontal polarization wave reflection coefficient, represents the transmission signal steering vector, represents the multipath steering vector of the transmitted signal, represents the reflection angle, It represents the phase difference caused by the path difference between the direct wave and the reflected wave. represents the vector product, represents the echo signal steering vector, represents the antenna array height, Indicates the projected distance between the antenna array and the height measurement target on the horizontal plane.

[0011] The beneficial effects of the above further scheme are as follows: the present invention eliminates the influence of multipath effect by using generalized multiple signal classification that is independent of the horizontal polarization wave reflection coefficient; the present invention solves the problem of mutual penetration between steering vectors by converting the multipath influence into a signal synthesized by a steering vector and using multiple signal classification including the horizontal polarization wave reflection coefficient, thereby improving the orthogonality between the noise subspace and the steering vector and ensuring the accuracy and reliability of angle estimation.

[0012] Furthermore, in S3, the order of estimating the initial value of the direct wave estimation angle and estimating the initial value of the horizontal polarization wave reflection estimation coefficient is alternately searched, and the steps of the alternate search are specifically as follows: In the first search, the random direct wave angle is used as the initial value to estimate the horizontal polarization wave reflection coefficient, and the initial estimate of the horizontal polarization wave transmission coefficient is obtained; The direct wave angle is estimated by using the initial estimated value of the horizontal polarization wave transmission coefficient as the initial value, so as to obtain the initial estimated value of the direct wave angle; In all searches except the first one, the reflection coefficient of the horizontally polarized wave is estimated using the current estimated value of the direct wave angle to obtain the next estimated value of the transmission coefficient of the horizontally polarized wave; The next estimated value of the horizontal polarization wave transmission coefficient is used to estimate the direct wave angle, and the next estimated value of the direct wave angle is obtained to realize alternating search.

[0013] The beneficial effect of the above further scheme is: the present invention reduces the amount of computational complexity of multi-dimensional multiple signal classification contraction by using alternating search to estimate the direct wave angle and the horizontal polarization wave reflection coefficient, effectively combines the generalized multiple signal classification algorithm and the multiple signal classification algorithm, improves the accuracy of the pitch angle wave arrival direction, and reduces the computational complexity.

[0014] Furthermore, the S4 is specifically as follows: The accuracy threshold is defined by the iteration accuracy, and the iteration threshold is defined by the maximum number of iterations; The estimation parameter group is judged using the accuracy threshold and the iteration threshold. If the accuracy of the estimation parameter group is less than the accuracy threshold or the number of iterations of the estimation parameter group is greater than the iteration threshold, the estimated angle is output, otherwise, return to step S3.

[0015] Furthermore, the expression for calculating the target height is as follows: ; in, Indicates the target height, represents the projected distance between the antenna array and the height measurement target, represents the estimated angle, Indicates the antenna array height.

[0016] The beneficial effect of the above further scheme is that the present invention selects the correct spectrum peaks and removes the false peaks in the spatial spectrum function, thereby avoiding the influence of redundant false spectrum peaks, improving the accuracy of the estimation method, and preventing the alternating search from falling into the local optimum. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The figure is a flow chart of the method of the present invention.

[0018] Figure 2 This is a model diagram obtained by modeling the multipath received signal of the meter-wave multi-input multi-output radar in this embodiment.

[0019] Figure 3 This is a diagram of the redundant spectral peak phenomenon in this embodiment.

[0020] Figure 4 Graph showing the relationship between the absolute value of the sum of the transmitted signal steering vector and the multipath steering vector and the direct wave angle at different wavelengths and antenna heights in this embodiment.

[0021] Figure 5 : is the mean square error diagram of angle measurement in this embodiment.

[0022] Figure 6 This is a graph of the mean square error of the height measurement in this embodiment. DETAILED DESCRIPTION

[0023] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0024] Before describing this embodiment, the following terms are explained: MIMO: Multiple Input Multiple Output; MUSIC: Multiple Signal Classification; DOA: Direction of Arrival; SNR: signal-to-noise ratio.

[0025] Example In this embodiment, in order to meet the needs of engineering implementation, the present invention proposes an alternating search method without decorrelation based on the generalized MUSIC algorithm and the MUSIC algorithm, and ensures that the pitch angle DOA has a high accuracy through iteration. At the same time, the spectrum peak search of the two algorithms is simplified to a one-dimensional search, which greatly reduces the computational complexity.

[0026] like Figure 1As shown, the present invention provides a multi-signal classification height measurement method based on meter-wave multi-input multi-output radar, and its implementation method is as follows: S1. According to the antenna array and the height measurement target, the multipath receiving signal of the meter-wave multi-input multi-output radar is modeled, and the received multi-input multi-output array receiving signal is matched filtered and vectorized to calculate the output signal. The specific steps are as follows: S101, modeling the multipath receiving signal of the meter-wave multi-input multi-output radar according to the antenna array and the height measurement target, and obtaining a multipath receiving signal model of the meter-wave multi-input multi-output radar; S102, obtaining a signal of the height measurement target being illuminated by the radar according to a transmission signal steering vector and a multipath steering vector of the transmission signal in a multi-path receiving signal model of a meter-wave multi-input multi-output radar; S103, obtaining an echo signal of a corresponding array element according to a signal of the height measurement target being illuminated by the radar and an array element of the antenna array, and obtaining a multi-input multi-output array receiving signal using the echo signal of each array element; S104, performing matched filtering and vectorization on the signals received by the multi-input multi-output array, and calculating and obtaining the output signals.

[0027] In this embodiment, Figure 2 As shown, considering M The transmit and receive co-located MIMO radar system has isotropic antennas. The array is a uniform linear array in the vertical direction. Without loss of generality, it is assumed that the electromagnetic wave polarization is horizontal polarization (the electromagnetic wave polarization will affect the calculation of the reflection coefficient and can be set according to actual conditions). Assume that the transmitted signal vector is: , The dimension is The complex domain value of , and the constraint expression is as follows: ; in, express M The unit matrix, represents the pulse width, represents the transmitted signal vector; exist Figure 2 middle, represents the direct wave angle, represents the reflection angle, Indicates the distance between the antenna array and the height measurement target, represents the projection distance between the antenna array and the height measurement target on the horizontal plane; and the multipath signal path of the distance between the antenna array and the height measurement target image is recorded as ; The antenna array of this embodiment is a single-base array with co-location of transmission and reception. Therefore, the transmission signal steering vector of the antenna array is equal to the echo signal steering vector, the multipath steering vector of the transmission signal is equal to the echo signal steering vector, and the signal of the height measurement target illuminated by the radar can be expressed as: ; ; ; ; in, A signal indicating that the height measuring target is illuminated by the radar. represents the transmission signal steering vector, represents the multipath steering vector of the transmitted signal, The multipath steering vector of the echo signal, represents the array element spacing, It represents the phase difference caused by the path difference between the direct wave and the reflected wave. represents the wavelength of electromagnetic waves, It represents the reflection coefficient of horizontal polarized wave related to the ground environment; Get the first m The expression of the echo signal received by each array element is as follows: ; in, Indicates m The echo signal received by each array element is represents the unknown deterministic complex constant, representing the reflection coefficient between different pulses of a single target, Indicates m The noise received by each array element; and the MIMO array receiving data is obtained from the echo signal received by the array element. The expression is as follows: ; in, indicates that the MIMO array receives data, and ; and matching filtering and vectorization are performed on the MIMO array received data to obtain an output signal, the expression of the output signal is as follows: ; in, represents the output signal, and , represents the vector product, Represents matrix vectorization.

[0028] In this embodiment, considering the noise situation, assuming that the noise received at the array edge is zero-mean Gaussian random white noise, the expression of the matched filter output result is as follows: ; in, represents the noise at the output of the matched filter, Represents the original noise vector; the output noise is still Gaussian white noise.

[0029] S2. Calculate the array data covariance according to the output signal and combine them into a covariance matrix. Obtain the noise subspace according to the covariance matrix. Use the generalized multiple signal classification method to obtain the initial value of the direct wave. Use the multiple signal classification method to obtain the initial value of the horizontal polarization wave reflection coefficient. The specific steps are as follows: S201, calculating array data covariance according to the output signal, combining the array data covariance into a covariance matrix, and performing eigendecomposition on the covariance matrix to obtain a noise subspace; S202, obtaining an initial value of the direct wave estimation angle using a generalized multiple signal classification method according to the noise subspace; S203, according to the multipath receiving signal model of the meter-wave multi-input multi-output radar, using the horizontal polarization wave reflection coefficient and the direct wave angle, calculating the steering vector of the received data, and according to multiple signal classification, using the steering vector of the received data and the noise subspace, obtaining the initial value of the horizontal polarization wave reflection estimation coefficient.

[0030] In this embodiment, the expression for calculating the array data covariance matrix is ​​as follows: ; in, represents the array data covariance matrix, Represents the output signal, Indicates the number of samples; And perform eigendecomposition on the array data covariance matrix to obtain the noise subspace ; According to the noise subspace First, we use the reflection coefficient that does not depend on horizontal polarization waves The generalized MUSIC is used to calculate the initial value of the direct wave estimated angle , the spatial spectrum function of the generalized MUSIC is: ; in, represents the determinant, Represents the steering matrix, and the arrival angle corresponding to the signal source is obtained at the peak of the spatial spectrum function, that is, the initial value of the direct wave estimation angle .

[0031] In this embodiment, in order to solve the problem that the mutual penetration between the transmission signal steering vector and the multipath steering vector of the transmission signal causes the orthogonality between the noise subspace and the steering vector to deteriorate, and ultimately reduces the accuracy and reliability of angle estimation, or even fails; the multipath influence is converted into a signal synthesized by the steering vector, that is, equivalent to the addition synthesis of the direct wave signal and the reflected wave signal. In addition, due to the geometric relationship between the direct wave and the reflected wave angle when the positive elevation angle is small, the expression of the reflection angle is as follows: ; in, represents the reflection angle, represents the antenna array height, Indicates the projection distance between the antenna array and the height measurement target on the horizontal plane; Then the steering vector of the received data can be rewritten as follows: ; in, represents the steering vector of the received data, represents the direct wave angle, represents the horizontal polarization wave reflection coefficient, represents the multipath steering vector of the transmitted signal, represents the reflection angle, It represents the phase difference caused by the path difference between the direct wave and the reflected wave. represents the vector product, represents the echo signal steering vector; According to the redefined steering vector of the received data, the covariance matrix is ​​calculated and the eigenvalue decomposition is performed to obtain the noise subspace. In this case, the MUSIC algorithm is used. At this time, the MUSIC algorithm only needs to be For a two-dimensional search, the expression of MUSIC is as follows: ; in, Represents the search space spectrum value of the direct wave angle and reflection coefficient; obtains the initial value of the horizontal polarization wave reflection estimation coefficient .

[0032] S3. According to the generalized multiple signal classification method and the multiple signal classification method, an alternate search is performed in the order of estimating the initial value of the direct wave estimation angle and the initial value of the estimated horizontal polarization wave reflection estimation coefficient in S2 to obtain an estimation parameter group including the direct wave estimation angle and the horizontal polarization wave reflection estimation coefficient.

[0033] In this embodiment, according to two parameters and The order of estimating the initial value is searched alternately to obtain the K The estimated parameter set of the sub-estimation ; Since the MUSIC algorithm has a huge amount of calculation for spectrum peak search, the alternating search is used to reduce the workload of the search; the alternating search is as follows: In the first search, the random direct wave angle is used as the initial value to estimate the horizontal polarization wave reflection coefficient, and the initial estimate of the horizontal polarization wave transmission coefficient is obtained; The direct wave angle is estimated by using the initial estimated value of the horizontal polarization wave transmission coefficient as the initial value, so as to obtain the initial estimated value of the direct wave angle; No. K The second search uses the direct wave angle The second estimated value is used to estimate the reflection coefficient of the horizontal polarization wave, and the second estimated value of the transmission coefficient of the horizontal polarization wave is obtained. K sub-estimates; Using the horizontal polarization wave transmission coefficient K The direct wave angle is estimated by the second estimated value, and the direct wave angle is obtained. K times the estimated value to achieve alternating search.

[0034] In this embodiment, when estimating the direct wave estimated angle, it is necessary to use generalized MUSIC to remove false peaks, as follows: In the one-dimensional search of the MUSIC algorithm, there are redundant large spectral peaks and periodic small spectral peaks, that is, false peaks. The phenomenon of MIMO radar lobe splitting is used to explain and solve the phenomenon of redundant spectral peaks, such as Figure 3 As shown in Figure 2, it can be seen that the smaller the pitch angle of the height measurement target is, the more obvious the influence of the periodic spectrum peak is, such as Figure 4 As shown, 20lgP represents the logarithmic processing of the search space spectrum value, and the absolute value of the sum of the transmission signal steering vector and the multipath steering vector when the horizontal polarization wave reflection coefficient is set to -0.9 ,in, Represents the steering vector of the transmitted signal Middle m elements, Represents the multipath steering vector of the transmitted signal Middle m elements; Figure 4It can be seen that as the wavelength decreases and the antenna height increases, the peak amplitude decreases, indicating that radars with larger wavelengths (wider beams) and lower antenna heights are more likely to have a beam "hitting the ground" phenomenon, resulting in serious lobe splitting. Therefore, in the embodiment, a smaller wavelength is selected and it is assumed that the antenna height is high enough and less than the height of the height measurement target, which can effectively avoid falling into the local optimal problem caused by redundant spectral peaks. However, sometimes the wavelength and antenna height of the radar are fixed due to other factors during system design and cannot be selected. Therefore, the present invention uses a generalized MUSIC method that is not affected by the position emission coefficient to select the correct spectral peak to avoid the occurrence of false redundant spectral peaks.

[0035] S4. Define the accuracy threshold and iteration threshold, and judge the estimated parameter group. If the accuracy of the estimated parameter group is less than the accuracy threshold or the number of iterations of the estimated parameter group is greater than the iteration threshold, output the direct wave estimation angle, otherwise return to step S3.

[0036] In this embodiment, the iteration accuracy is used Defining the accuracy threshold , and use the maximum number of iterations to define the iteration threshold; use the accuracy threshold and iteration threshold to judge the estimated parameter group. If the accuracy of the estimated parameter group is less than the accuracy threshold, Or the number of iterations of the estimated parameter group is greater than the iteration threshold , output the estimated angle, otherwise return to the alternating search step to obtain the estimated parameter value.

[0037] S5. Use the direct wave to estimate the angle, and combine the projection distance between the antenna array and the height measurement target in the multi-path receiving signal model of the meter-wave multi-input multi-output radar and the height of the antenna array to calculate the target height and complete the multi-signal classification height measurement.

[0038] In this embodiment, the incident direct wave is taken as , signal-to-noise ratio Conduct experiments and define the mean square error as follows: ; in, Indicates the parameter to be measured, represents the number of Monte Carlo random experiments; 100 Monte Carlo experiments are performed at each incident angle at each SNR value, the number of array elements M=10, the number of snapshots is 10, , , , as well as The MUSIC algorithm is simulated under the condition of Figure 5 The mean square error of the angle measurement is shown as Figure 6From the mean square error of height measurement shown in the figure, it can be found that the angle measurement accuracy is higher under high signal-to-noise ratio and large elevation angle conditions. However, due to the characteristics of the meter-wave radar lobe splitting, the angle measurement accuracy is lower in the low elevation angle area.

[0039] In the present embodiment, under a relatively ideal model, the altimetry problem of meter-wave MIMO radar is analyzed, and the redundant spectrum peak problem of the guidance vector synthesis algorithm is found, and a method for low-elevation-angle altimetry of meter-wave MIMO radar combining generalized MUSIC and MUSIC alternately searching is proposed, which avoids the problem of a sharp increase in the amount of calculation caused by dense grid division search, and achieves a good low-elevation-angle altimetry effect. The method of the present invention does not need to be decoherent, has a high engineering practical value, and the signal model constructed by the present invention is relatively ideal.

Claims

1. A multi-signal classification height measurement method based on meter-wave multi-input multi-output radar, characterized in that: The following steps are involved: S1. Model the multipath receiving signal of the meter-wave multi-input multi-output radar according to the antenna array and the height measurement target, perform matched filtering and vectorization on the received multi-input multi-output array receiving signal, and calculate the output signal; S2. Calculate the array data covariance according to the output signal and combine them into a covariance matrix, obtain the noise subspace according to the covariance matrix, use the generalized multiple signal classification method to obtain the initial value of the direct wave, and use the multiple signal classification to obtain the initial value of the horizontal polarization wave reflection coefficient; S3, according to the generalized multiple signal classification method and the multiple signal classification method, an alternate search is performed in the order of estimating the initial value of the direct wave estimation angle and estimating the initial value of the horizontal polarization wave reflection estimation coefficient in S2 to obtain an estimation parameter group including the direct wave estimation angle and the horizontal polarization wave reflection estimation coefficient; S4, define the accuracy threshold and iteration threshold, and judge the estimated parameter group. If the accuracy of the estimated parameter group is less than the accuracy threshold or the number of iterations of the estimated parameter group is greater than the iteration threshold, output the direct wave estimation angle, otherwise return to step S3; S5. Use the direct wave to estimate the angle, and combine the projection distance between the antenna array and the height measurement target in the multi-path receiving signal model of the meter-wave multi-input multi-output radar and the height of the antenna array to calculate the target height and complete the multi-signal classification height measurement.

2. The method for measuring altitude by multiple signal classification based on meter-wave multi-input multi-output radar according to claim 1, characterized in that: The S1 comprises the following steps: S101, modeling the multipath receiving signal of the meter-wave multi-input multi-output radar according to the antenna array and the height measurement target; S102, obtaining a signal of the height measurement target being illuminated by the radar according to a transmission signal steering vector and a multipath steering vector of the transmission signal in a multi-path receiving signal model of a meter-wave multi-input multi-output radar; S103, obtaining an echo signal of a corresponding array element according to a signal of the height measurement target being illuminated by the radar and an array element of the antenna array, and obtaining a multi-input multi-output array receiving signal using the echo signal of each array element; S104, performing matched filtering and vectorization on the signals received by the multi-input multi-output array, and calculating and obtaining the output signals.

3. The method for measuring altitude by multiple signal classification based on meter-wave multi-input multi-output radar according to claim 1, characterized in that: The S2 comprises the following steps: S201, calculating array data covariance according to the output signal, combining the array data covariance into a covariance matrix, and performing eigendecomposition on the covariance matrix to obtain a noise subspace; S202, obtaining an initial value of the direct wave estimation angle using a generalized multiple signal classification method according to the noise subspace; S203, according to the multipath receiving signal model of the meter-wave multi-input multi-output radar, using the horizontal polarization wave reflection coefficient and the direct wave angle, calculating the steering vector of the received data, and according to multiple signal classification, using the steering vector of the received data and the noise subspace, obtaining the initial value of the horizontal polarization wave reflection estimation coefficient.

4. The method for measuring altitude by multiple signal classification based on meter-wave multi-input multi-output radar according to claim 3 is characterized in that: The expression of the multiple signal classification is as follows: in, represents the search space spectrum value of direct angle and reflection coefficient, represents the steering vector of the received data, represents the direct wave angle, represents the horizontal polarization wave reflection coefficient, represents the transmission signal steering vector, represents the multipath steering vector of the transmitted signal, represents the reflection angle, It represents the phase difference caused by the path difference between the direct wave and the reflected wave. represents the vector product, represents the echo signal steering vector, represents the antenna array height, Indicates the projected distance between the antenna array and the height measurement target on the horizontal plane.

5. The method for measuring altitude by multiple signal classification based on meter-wave multi-input multi-output radar according to claim 1, characterized in that: In S3, the order of estimating the initial value of the direct wave estimation angle and estimating the initial value of the horizontal polarization wave reflection estimation coefficient is alternately searched, and the steps of the alternate search are specifically as follows: In the first search, the random direct wave angle is used as the initial value to estimate the horizontal polarization wave reflection coefficient, and the initial estimate of the horizontal polarization wave transmission coefficient is obtained; The direct wave angle is estimated by using the initial estimated value of the horizontal polarization wave transmission coefficient as the initial value, so as to obtain the initial estimated value of the direct wave angle; In searches other than the first one, the reflection coefficient of the horizontally polarized wave is estimated using the current estimated value of the direct wave angle to obtain the next estimated value of the transmission coefficient of the horizontally polarized wave; The next estimated value of the horizontal polarization wave transmission coefficient is used to estimate the direct wave angle, and the next estimated value of the direct wave angle is obtained to realize alternating search.

6. The method for measuring altitude by multiple signal classification based on meter-wave multi-input multi-output radar according to claim 1, characterized in that: The specific steps of S4 are as follows: The accuracy threshold is defined by the iteration accuracy, and the iteration threshold is defined by the maximum number of iterations; The estimation parameter group is judged using the accuracy threshold and the iteration threshold. If the accuracy of the estimation parameter group is less than the accuracy threshold or the number of iterations of the estimation parameter group is greater than the iteration threshold, the estimated angle is output, otherwise, return to step S3.

7. The method for measuring altitude by multiple signal classification based on meter-wave multi-input multi-output radar according to claim 1, characterized in that: The expression for calculating the target height is as follows: in, Indicates the target height, represents the projected distance between the antenna array and the height measurement target, represents the estimated angle, Indicates the antenna array height.

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