Meter-wave MIMO radar height measurement method under complex terrain conditions

Abstract

The present invention discloses a method for measuring the height of a meter-wave MIMO radar under complex terrain conditions. Aiming at the problem of measuring the height of a meter-wave MIMO radar system under an actual complex position environment, a signal model that considers factors such as multiple reflection points, ground undulations, and ground reflective media is proposed. For the signal model, a generalized MUSIC or maximum likelihood estimation algorithm is used to calculate the target elevation angle. The signal model established in the present invention is closer to the actual terrain and more refined, and the method can estimate the target elevation angle and height parameters without any prior information such as known reflection coefficients and wave path differences. The studied height measurement method is less affected by complex terrain and has good position adaptability and robustness.

Description

Technical Field

[0001] The invention relates to the technical field of meter-wave MIMO radar height measurement, and in particular to a meter-wave MIMO radar height measurement method under complex terrain conditions. Background Art

[0002] MIMO radar has waveform diversity, which gives it many advantages over conventional phased array radar, especially in the field of angle estimation. MIMO radar angle estimation has achieved relatively rich estimation results, and classic super-resolution algorithms such as ESPRIT, MUSIC, ML, etc. have been applied, including advanced signal processing technologies based on compressed sensing and sparse representation.

[0003] There is a special type of problem in MIMO radar angle estimation, that is, the low-elevation-angle height measurement problem of meter-wave MIMO radar. Due to the presence of multipath reflection signals in the low-elevation area, height measurement becomes a difficult problem in parameter estimation. For the convenience of analysis, many scholars assume that the reflecting ground is flat and have studied many height measurement methods, such as the generalized MUSIC height measurement method, the maximum likelihood estimation height measurement method, and the BOMP algorithm. These methods are based on polarization information, frequency diversity technology, sparse dictionary, adaptive beamforming, lobe resolution algorithm, and multipath energy utilization. When the reflecting ground is flat, these methods have achieved good height measurement accuracy. However, it is worth noting that there are many complex terrains in actual terrain, such as undulating terrain and inclined terrain. In addition, the signal models used in the above height measurement methods all assume that there is only one reflection point, and as the target moves in a complex environment, there is a high probability that there will be more than one reflection point. Therefore, the accuracy of the above height measurement algorithms is greatly reduced in actual applications. The reason is mainly due to the mismatch between the height measurement algorithm and the actual terrain, that is, the established signal model and the actual terrain signal model are mismatched. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention aims to provide a method for meter-wave MIMO radar altimetry under complex terrain conditions, establish a refined signal model, which takes into account the terrain undulation and inclination conditions, and assumes that there are multiple reflection points. Based on the signal model, a generalized MUSIC algorithm or a maximum likelihood estimation algorithm is used to calculate the target elevation angle, which is less affected by complex terrain and has good position adaptability and robustness.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] The method for measuring the height of a meter-wave MIMO radar under complex terrain conditions is characterized by comprising the following steps:

[0007] S1: Establish the signal model of meter-wave MIMO radar system under complex terrain conditions;

[0008] S2: Based on the meter-wave MIMO radar system signal model established in step S1, use the generalized MUSIC algorithm or the maximum likelihood estimation algorithm to measure the height and obtain the target elevation angle.

[0009] Furthermore, the specific operation of step S1 includes the following steps:

[0010] S101: Under the condition that the meter-wave MIMO radar system composed of uniform linear array is placed vertically, a terrain multipath reflection model is established, wherein the transmitting and receiving array elements of the meter-wave MIMO radar system are shared, the number of array elements is M, the distance between adjacent array elements is d=λ / 2, and h a is the reference element height, h t is the target height, θ q，i is the ground inclination angle of the i-th reflection point, θ s，i is the arrival direction of the reflected wave of the i-th reflection path;

[0011] S102: Establishing a signal model where the direct wave of the signal transmitted by the mth antenna array element reaches the target;

[0012] S103: Establishing a signal model when the signal transmitted by the mth antenna array element reaches the target after being reflected by the ith reflection point;

[0013] S104: Establishing a total signal model where the signal transmitted by the mth antenna array element reaches the target;

[0014] S105: Establishing a total signal model where the signals transmitted by all antenna elements of the MIMO radar system reach the target.

[0015] Furthermore, the specific operation of step S102 includes the following steps:

[0016] S1021: Assume that the transmission signal of the mth antenna array element at time t is

[0017]

[0018] Where f0 is the center frequency, φ m is the initial phase of the transmitted signal, and φ m =0;s m (t) is the complex envelope of the transmitted signal of the mth array element, which is p All are unit energy; j = (-1) 0.5 , is the complex imaginary part;

[0019] S1022: Establish a signal model where the direct wave of the signal transmitted by the mth antenna array element reaches the target:

[0020]

[0021] Among them, τ d，m =R d，m / c is the time delay between the direct wave and the mth array element, c is the speed of light, c = 3*108m / s; R d，m is the distance between the target and the mth array element

[0022]

[0023] In the formula, h m is the height of the mth antenna array element, R is the distance between the projection point of the radar system to the horizontal ground and the target, R r is the horizontal distance between the radar system and the target, θ d To reach Cape Popoda directly.

[0024] Furthermore, the specific operation of step S103 includes the following steps:

[0025] S1031: Establish a signal model when the mth antenna array element reaches the target after being reflected by the ith reflection point

[0026]

[0027] Among them, ρ si is the reflection coefficient of the i-th reflection point, τ si，m =R si，m / cThe time delay between the reflected wave of the ith reflection path and the mth array element, R si，m is the distance traveled by the reflected wave of the i-th reflection path;

[0028] S1032: Use horizontal polarization wave to calculate the reflection coefficient ρ of the i-th reflection point si Expressed as

[0029] ρ si =ρ i ρ D ζ i (5)

[0030] in,

[0031]

[0032]

[0033]

[0034] In the formula, ρ D is the divergence factor, R Eis the radius of the earth; r1 is the arc length distance between the projection of the radar system to the ground and the reflection point, r2 is the surface distance from the reflection point to the vertical projection of the target, r = r1 + r2, ψ is the ground rubbing angle, and the ground rubbing angle of the i-th reflection point is expressed as ψ i ;ζ i is the surface roughness factor of the i-th reflection point, and its value is related to ψ i , ground relief variance σ h It is related to the wavelength λ, I is the number of reflection points; ρ i is the Fresnel reflection coefficient of the i-th reflection point, ε i is the complex dielectric constant of the ground of the i-th reflection path;

[0035] S1033: Based on step S1032, the distance R traveled by the reflected wave of the i-th reflection path si，m The expression is

[0036]

[0037] In the formula, h s，i is the height of the i-th reflection point, which is negative when it is above the horizontal line and positive when it is below the horizontal line, and

[0038]

[0039] Among them, R b is the distance between the reflection point and the projection of the antenna element on the ground.

[0040] Furthermore, the specific operation of step S104 includes the following steps:

[0041] S1041: Establishing a total signal model of the direct wave and reflected wave of the signal transmitted by the mth antenna array element to the target

[0042]

[0043] S1042: Since the MIMO radar transmits a narrowband signal, the time shift will not affect the complex envelope of the signal, that is,

[0044] s m (t-τ d，m )≈s m (t-τ si，m )=s m (t) (12);

[0045] S1043: Combining steps S1041 and S1042, we can get

[0046]

[0047] In the formula,

[0048] θ s，i ≈-(arctan(tanθ d +2h a / R)+θ q，i ) (14)

[0049] Among them, ΔR i is the path difference between the direct wave and the reflected wave;

[0050] S1044: Use the binomial theorem to convert R si，m and R d，m Expanding, the path difference between the direct wave and the reflected wave is

[0051] ΔR i =R si，m -R d，m ≈R+(h t +h m +2h s，i ) 2 / 2R-(R+(h t -h m ) 2 / 2R)

[0052] =2h t h m +2h s，i (h s，i +h t +h m ) / R (15);

[0053] S1045: Substituting formula (15) and λ=c / f into formula (13), we can obtain

[0054]

[0055] In the formula,

[0056] Furthermore, the specific operation of step S105 includes the following steps:

[0057] S1051: Establish the overall signal model of the MIMO radar system where all antenna elements transmit signals and reach the target

[0058]

[0059] In the formula, δ i =2πΔR i / λ,s(t)=[s1(t),...,s M (t)] T is the transmission signal of the MIMO radar system, a t (θ d ), at (θ s，i ) are the guiding vectors of the direct wave and the reflected wave, respectively, and their expressions are

[0060]

[0061]

[0062] S1052: Considering the reflection multipath, the principle is the same as the transmission multipath. Then the data received by all receiving elements of the MIMO radar system is

[0063]

[0064] Where n(t) is Gaussian white noise with a mean of 0 and a variance of

[0065] S1053: Perform matched filtering on the data received by all receiving elements of the MIMO radar system.

[0066]

[0067] By vectorizing equation (20), we can get

[0068]

[0069] Furthermore, the specific operation of step S2 includes the following steps:

[0070] S201: Set the number of reflection points I = 2, simplify formula (21), and then

[0071]

[0072] In the formula,

[0073]

[0074]

[0075] Among them, A(θ d ,θ s，1 ,θ s，2 ) is the steering vector of the radar system receiving data, θ s，1 ,θ s，2 are the arrival angles of the first and second reflected waves, respectively;

[0076] S202: Obtain the covariance matrix of the complex terrain receiving data according to the maximum likelihood estimation criterion

[0077]

[0078] Where R is the data covariance matrix, L is the number of snapshots, and Y is the complex terrain received data. H represents the matrix transpose conjugate;

[0079] S203: Calculate the target elevation angle using the generalized MUSIC algorithm or the maximum likelihood method.

[0080] Furthermore, the generalized MUSIC algorithm in step S203 is specifically as follows: the covariance matrix of the complex terrain received data is subjected to eigenvalue decomposition to obtain the noise subspace E n , the terrain-adaptive generalized MUSIC spectrum peak search formula is further expressed as

[0081]

[0082] The angle estimate corresponding to the spectrum peak is the target elevation angle.

[0083] Furthermore, the maximum likelihood method in step S203 is specifically as follows: the terrain is scouted to obtain the terrain inclination parameter, then the maximum likelihood estimation value of the target elevation angle, that is, the target elevation angle is

[0084]

[0085] Where P A(θ) is the projection matrix formed by projecting the column vectors onto the steering vector matrix A(θ),

[0086] P A(θ) =A(θ)[A H (θ)A(θ)] -1 A H (0) (28).

[0087] The beneficial effects of the present invention are:

[0088] 1. The method for measuring the height of a meter-wave MIMO radar under complex terrain conditions in the present invention proposes a signal model that takes into account factors such as multiple reflection points, ground undulations, and ground reflection media, and uses generalized MUSIC or maximum likelihood estimation to calculate the target elevation angle. The signal model established in the present invention is closer to the actual terrain and more refined. The simulation experiment shows that the accuracy of the unmatched algorithm in the present invention is extremely poor, and the accuracy of the matched algorithm is improved.

[0089] 2. The meter-wave MIMO radar altimetry method under complex terrain conditions in the present invention solves the problem of meter-wave MIMO radar guidance vector coupling, and the method can estimate the target elevation angle and altitude parameters without any prior information such as known reflection coefficient and wave path difference. The altimetry method studied is less affected by complex terrain and has good position adaptability and robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Figure 1 It is a schematic diagram of the terrain multipath reflection model in the present invention.

[0091] Figure 2 This is the spectrum peak search diagram of the matching and non-matching algorithms in the simulation experiment 1 of the present invention.

[0092] Figure 3 This is a graph showing the variation of RMSE with signal-to-noise ratio in the second simulation experiment of the present invention.

[0093] Figure 4 This is a graph showing how RMSE changes with the number of snapshots in the third simulation experiment of the present invention. DETAILED DESCRIPTION

[0094] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0095] Embodiment 1:

[0096] The method for measuring the height of a meter-wave MIMO radar under complex terrain conditions includes the following steps:

[0097] S1: Establish the signal model of meter-wave MIMO radar system under complex terrain conditions;

[0098] S2: Based on the meter-wave MIMO radar system signal model established in step S1, a generalized MUSIC algorithm or a maximum likelihood algorithm is used to measure the height to obtain the target elevation angle.

[0099] Specifically, the specific operation of step S1 includes the following steps:

[0100] S101: Consider a meter-wave MIMO radar system composed of a vertically placed uniform linear array. Under the condition that the meter-wave MIMO radar system composed of a vertically placed uniform linear array is placed, a terrain multipath reflection model is established, as shown in the attached figure. Figure 1 As shown. The transmitting and receiving array elements of the meter-wave MIMO radar system are shared, the number of array elements is M, the distance between adjacent array elements is d = λ / 2, and h a is the reference element height (set as the minimum element height in the present invention), h t is the target height, θ q，i is the ground inclination angle of the i-th reflection point, θ s，i is the arrival direction of the reflected wave of the i-th reflection path, B and C represent the reflection points of the two reflection paths;

[0101] Further, S102: establishing a signal model of the direct wave of the signal transmitted by the mth antenna array element reaching the target;

[0102] More specifically, S1021: Assume that the transmission signal of the mth antenna array element at time t is

[0103]

[0104] Where f0 is the center frequency, φ m is the initial phase of the transmitted signal, and φ m =0;s m (t) is the complex envelope of the transmitted signal of the mth array element, which is p All are unit energy; j = (-1) 0.5 , is the complex imaginary part;

[0105] S1022: Establish a signal model where the direct wave of the signal transmitted by the mth antenna array element reaches the target:

[0106]

[0107] Among them, τ d，m =R d，m / c is the time delay between the direct wave and the mth array element, c is the speed of light, c = 3*108m / s; R d，m is the distance between the target and the mth array element. Through geometric relationship, its expression can be obtained as

[0108]

[0109] In the formula, h m is the height of the mth antenna array element, R is the distance between the projection point of the radar system to the horizontal ground and the target, R r is the horizontal distance between the radar system and the target, θ d To reach Cape Popoda directly.

[0110] Further, S103: establishing a signal model when the signal transmitted by the mth antenna array element reaches the target after being reflected by the ith reflection point;

[0111] More specifically, S1031: Establish a signal model when the mth antenna array element reaches the target after being reflected by the ith reflection point

[0112]

[0113] Among them, ρ si is the reflection coefficient of the i-th reflection point, τ si，m =R si，m / c The time delay between the reflected wave of the ith reflection path and the mth array element, S si，m is the distance traveled by the reflected wave of the i-th reflection path;

[0114] S1032: Use horizontal polarization wave to calculate the reflection coefficient ρ of the i-th reflection point si Expressed as

[0115] ρ si =ρ i ρ D ζ i (5)

[0116] in,

[0117]

[0118]

[0119]

[0120] In the formula, ρ D is the divergence factor, R E is the radius of the earth; r1 is the arc length distance between the projection of the radar system to the ground and the reflection point, r2 is the surface distance from the reflection point to the vertical projection of the target, r = r1 + r2, ψ is the ground rubbing angle, and the ground rubbing angle of the i-th reflection point is expressed as ψ i ; In the low elevation angle region, the divergence factor is generally approximately equal to 1. ζ i is the surface roughness factor of the i-th reflection point, and its value is related to the rubbing angle ψ of the i-th reflection point i , ground relief variance σ h It is related to the wavelength λ, I is the number of reflection points; ρ i is the Fresnel reflection coefficient of the i-th reflection point, and its value is related to the ground reflection medium; ε i is the complex dielectric constant of the ground of the i-th reflection path;

[0121] S1033: Based on step S1032, the distance R traveled by the reflected wave of the i-th reflection path si，m The expression is

[0122]

[0123] In the formula, h s，i is the height of the i-th reflection point, which is negative when it is above the horizontal line and positive when it is below the horizontal line, and

[0124]

[0125] Among them, R b is the distance between the reflection point and the projection of the antenna element on the ground.

[0126] Further, S104: establishing a total signal model of the signal transmitted by the mth antenna array element reaching the target;

[0127] More specifically, S1041: Establish a total signal model of the direct wave and the reflected wave of the signal transmitted by the mth antenna array element to the target.

[0128]

[0129] S1042: Since the MIMO radar transmits a narrowband signal, the time shift will not affect the complex envelope of the signal, that is,

[0130] s m (t-τ d，m )≈s m (t-τ si，m )=s m (t) (12);

[0131] S1043: Combining steps S1041 and S1042, we can get

[0132]

[0133] From the geometric relationship, we can get:

[0134] θ s，i ≈-(arctan(tanθ d +2h a / R)+θ q，i ) (14)

[0135] Among them, ΔR i is the path difference between the direct wave and the reflected wave;

[0136] S1044: Use the binomial theorem to convert R si，m and R d，m Expand (due to R>>h a ,h t , so we discard the higher-order terms and only consider the first two terms), then the path difference between the direct wave and the reflected wave is

[0137]

[0138] S1045: Substituting formula (15) and λ=c / f into formula (13), we can obtain

[0139]

[0140] In the formula,

[0141] Further, S105: establishing a total signal model of the signals transmitted by all antenna elements of the MIMO radar system reaching the target;

[0142] More specifically, S1051: Establishing a total signal model for the arrival of signals transmitted by all antenna elements of the MIMO radar system at the target

[0143]

[0144] In the formula, δ i =2πΔR i / λ,s(t)=[s1(t),...,s M (t)] T is the transmission signal of the MIMO radar system, a t (θ d ), a t (θ s，i ) are the guiding vectors of the direct wave and the reflected wave, respectively, and their expressions are

[0145]

[0146]

[0147] S1052: The above considerations are for transmit multipath. Based on the reciprocity, it is not difficult to know that there is reflective multipath. Its principle is the same as that of transmit multipath. Therefore, the data received by all receiving elements of the MIMO radar system is:

[0148]

[0149] Where n(t) is Gaussian white noise with a mean of 0 and a variance of

[0150] S1053: Perform matched filtering on the data received by all receiving elements of the MIMO radar system.

[0151]

[0152] By vectorizing equation (20), we can get

[0153]

[0154] Furthermore, it can be concluded from the above step S1 that the difference between the received signal model of the meter-wave MIMO radar studied in the present invention and the received signal model of the flat terrain mainly lies in the difference in the wave path difference, reflection coefficient and reflection angle. Therefore, the generalized MUSIC algorithm adapted to the terrain needs to match the signal model studied in the above parameters. On this basis, the specific operation of step S2 includes the following steps:

[0155] S201: Set the number of reflection points I = 2, simplify formula (21), and then

[0156]

[0157] In the formula,

[0158]

[0159]

[0160] Among them, A(θ d ,θ s，1 ,θ s，2 ) is the guidance vector of the radar system receiving data. It is not difficult to find that it contains three unknown parameters, θ s，1 ,θ s，2 are the arrival angles of the first and second reflected waves respectively; (when the number of actual reflection points increases, the number of unknown parameters increases accordingly); θ d ,θ s，1 and θ s，2 There is a relationship as shown in formula (24). If the steering vector matches the terrain, it is necessary to scout the terrain in advance to obtain the inclination parameters of the terrain. At this time, A(θ d ,θ s，1 ,θ s，2 ) becomes one unknown parameter, which can be written as A(θ d ).

[0161] S202: Obtain the covariance matrix of the complex terrain receiving data according to the maximum likelihood estimation criterion

[0162]

[0163] Where R is the data covariance matrix, L is the number of snapshots, and Y is the complex terrain received data. H represents the matrix transpose conjugate;

[0164] S203: Use the generalized MUSIC algorithm to calculate the target elevation angle. Specifically, perform eigenvalue decomposition on the covariance matrix of the complex terrain receiving data to obtain the noise subspace E n , which is the same as the principle of the flat terrain spectrum peak search formula, the generalized MUSIC spectrum peak search formula adapted to the terrain is further expressed as

[0165]

[0166] The angle estimate corresponding to the spectrum peak is the target elevation angle.

[0167] Embodiment 2:

[0168] The difference between the second embodiment and the first embodiment is only in step S203. In the second embodiment, the maximum likelihood estimation algorithm is used to calculate the target elevation angle. Specifically,

[0169] The terrain inclination parameters are obtained by terrain reconnaissance, and the maximum likelihood estimation spectrum peak of the target elevation angle is

[0170]

[0171] Where P A(θ) is the projection matrix formed by projecting the column vectors onto the steering vector matrix A(θ),

[0172] P A(θ) =A(θ)[A H (θ)] -1 A H (θ) (28).

[0173] Simulation experiment:

[0174] The present invention mainly compares the performance of the two algorithms in the embodiment and the second embodiment when the terrain is matched and the terrain is not matched. When not defined again, the parameters of the present invention are set as follows: the number of transmitting array elements M=N=10, the radar operating frequency is 300MHz, the signal-to-noise ratio SNR=10dB, the number of snapshots L=50, the target elevation angle θ d =3°, the inclination angle θ of the first reflection point q，1 =2°, height h s，i =1m, the inclination angle θ of the second reflection point q，2＝ 3°, height h s，i =2m, standard deviation of overall terrain relief σ h =2m, the reflection media of the two reflection points are dry soil and wet soil respectively, the array element spacing is λ / 2, and the number of experiments K=500.

[0175] Experiment 1: This experiment is a spectrum peak search diagram of the two algorithms when the terrain matches and does not match. The results are shown in the attached Figure 2 As shown in the attached Figure 2 It can be seen that when the terrain matches, the two algorithms can correctly estimate the target elevation angle, but when the terrain does not match, the two algorithms cannot estimate the target elevation angle.

[0176] Experiment 2: This experiment verifies the relationship between the matching algorithm and the mismatching algorithm and the signal-to-noise ratio. The signal-to-noise ratio range is [-10dB, 10dB]. The results are shown in the attached Figure 3 As shown in the attached Figure 3 It can be seen that when the terrain does not match, when the signal-to-noise ratio increases, the angle RMSE and height RMSE of the two algorithms are large and almost unchanged, which means that when the terrain does not match, the accuracy of the two algorithms is almost invalid. When the terrain matches, the angle RMSE and height RMSE of the two algorithms decrease as the signal-to-noise ratio increases, and have good accuracy, which means that when the terrain matches, the two algorithms can correctly estimate the target elevation angle.

[0177] Experiment 3: The purpose of this experiment is to verify the relationship between the matching algorithm and the mismatching algorithm and the number of snapshots. The number of snapshots ranges from [30, 210], and the signal-to-noise ratio SNR = 0dB. The results are shown in the attached figure. Figure 4 As shown in the attached Figure 4 It can be seen that when the terrain does not match, as the number of snapshots increases, the angle RMSE and height RMSE of the two algorithms are large and almost unchanged, which also shows that when the terrain does not match, the accuracy of the two algorithms is almost invalid. When the terrain matches, the angle RMSE and height RMSE of the two algorithms decrease as the number of snapshots increases, and have good accuracy, which shows that when the terrain matches, the two algorithms can correctly estimate the target elevation angle.

[0178] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for measuring the height of a meter-wave MIMO radar under complex terrain conditions, characterized in that: The following steps are included: S1: Establish the signal model of meter-wave MIMO radar system under complex terrain conditions; S2: Based on the meter-wave MIMO radar system signal model established in step S1, a generalized MUSIC algorithm or a maximum likelihood estimation algorithm is used to measure the height and obtain the target elevation angle; The specific operation of step S1 includes the following steps: S101: Under the condition that the meter-wave MIMO radar system composed of uniform linear array is placed vertically, a terrain multipath reflection model is established, wherein the transmitting and receiving array elements of the meter-wave MIMO radar system are shared, the number of array elements is M, the distance between adjacent array elements is d=λ / 2, and h a is the reference element height, h t is the target height, θ q，i is the ground inclination angle of the i-th reflection point, θ s,i is the arrival direction of the reflected wave of the i-th reflection path; S102: Establishing a signal model where the direct wave of the signal transmitted by the mth antenna array element reaches the target; S103: Establishing a signal model when the signal transmitted by the mth antenna array element reaches the target after being reflected by the ith reflection point; S104: Establishing a total signal model where the signal transmitted by the mth antenna array element reaches the target; S105: Establishing a total signal model where signals transmitted by all antenna elements of the MIMO radar system reach the target; The specific operation of step S105 includes the following steps: S1051: Establish the overall signal model of the MIMO radar system where all antenna elements transmit signals and reach the target Where I is the number of reflection points; ρ si is the reflection coefficient of the i-th reflection point, j = (-1) 0.5 , is the complex imaginary part; δ i =2πΔR i / λ, ΔR i is the path difference between the direct wave and the reflected wave; s(t)=[s1(t),...,s M (t)] T is the transmission signal of the MIMO radar system, a t (θ d ), a t (θ s，i ) are the guiding vectors of the direct wave and the reflected wave, respectively, and their expressions are R is the distance between the projection point of the radar system to the horizontal ground and the target, θ d To reach Cape Popoda directly; S1052: Considering the reflection multipath, the principle is the same as the transmission multipath. Then the data received by all receiving elements of the MIMO radar system is Where n(t) is Gaussian white noise with a mean of 0 and a variance of S1053: Perform matched filtering on the data received by all receiving elements of the MIMO radar system. By vectorizing equation (20), we can get The specific operation of step S2 includes the following steps: S201: Set the number of reflection points I = 2, simplify formula (21), and then In the formula, Among them, A(θ d ,θ s，1 ,θ s，2 ) is the steering vector of the radar system receiving data, θ s，1 ,θ s，2 are the arrival angles of the first and second reflected waves, respectively; S202: Obtain the covariance matrix of the complex terrain receiving data according to the maximum likelihood estimation criterion Where R is the data covariance matrix, L is the number of snapshots, and Y is the complex terrain received data. H represents the matrix transpose conjugate; S203: Calculate the target elevation angle using the generalized MUSIC algorithm or the maximum likelihood method.

2. The method for measuring altitude of meter-wave MIMO radar under complex terrain conditions according to claim 1, characterized in that: The specific operation of step S102 includes the following steps: S1021: Assume that the transmission signal of the mth antenna array element at time t is Where f0 is the center frequency, φ m is the initial phase of the transmitted signal, and φ m =0;s m (t) is the complex envelope of the transmitted signal of the mth array element, which is p All are unit energy; j = (-1) 0.5 , is the complex imaginary part; S1022: Establish a signal model where the direct wave of the signal transmitted by the mth antenna array element reaches the target: Among them, τ d，m =R d，m / c is the time delay between the direct wave and the mth array element, c is the speed of light, c = 3*10 8 m / s; R d，m is the distance between the target and the mth array element In the formula, h m is the height of the mth antenna array element, R is the distance between the projection point of the radar system to the horizontal ground and the target, R r is the horizontal distance between the radar system and the target, θ d To reach Cape Popoda directly.

3. The method for measuring altitude of meter-wave MIMO radar under complex terrain conditions according to claim 2, characterized in that: The specific operation of step S103 includes the following steps: S1031: Establish a signal model when the mth antenna array element reaches the target after being reflected by the ith reflection point Among them, ρ si is the reflection coefficient of the i-th reflection point, τ si，m =R si，m / cThe time delay between the reflected wave of the ith reflection path and the mth array element, R si，m is the distance traveled by the reflected wave of the i-th reflection path; S1032: Use horizontal polarization wave to calculate the reflection coefficient ρ of the i-th reflection point si Expressed as r si =ρ i r D g i (5) in, In the formula, ρ D is the divergence factor, R E is the radius of the earth; r1 is the arc length distance between the projection of the radar system to the ground and the reflection point, r2 is the surface distance from the reflection point to the vertical projection of the target, r = r1 + r2, ψ is the ground rubbing angle, and the ground rubbing angle of the i-th reflection point is expressed as ψ i ;ζ i is the surface roughness factor of the i-th reflection point, and its value is related to ψ i , ground relief variance σ h It is related to the wavelength λ, I is the number of reflection points; ρ i is the Fresnel reflection coefficient of the i-th reflection point, ε i is the complex dielectric constant of the ground of the i-th reflection path; S1033: Based on step S1032, the distance R traveled by the reflected wave of the i-th reflection path si,m The expression is In the formula, h s,i is the height of the i-th reflection point, which is negative when it is above the horizontal line and positive when it is below the horizontal line, and Among them, R b is the distance between the reflection point and the projection of the antenna element on the ground.

4. The method for measuring altitude of meter-wave MIMO radar under complex terrain conditions according to claim 3, characterized in that: The specific operation of step S104 includes the following steps: S1041: Establishing a total signal model of the direct wave and reflected wave of the signal transmitted by the mth antenna array element to the target S1042: Since the MIMO radar transmits a narrowband signal, the time shift will not affect the complex envelope of the signal, that is, s m (t-t d,m )≈s m (t-t si,m )=s m (t) (12); S1043: Combining steps S1041 and S1042, we can get In the formula, θ s，i ≈-(arctan(tanθ d +2h a / R)+θ q，i ) (14) Among them, ΔR i is the path difference between the direct wave and the reflected wave; S1044: Use the binomial theorem to convert R si，m and R d，m Expanding, the path difference between the direct wave and the reflected wave is S1045: Substituting formula (15) and λ=c / f into formula (13), we can obtain In the formula, 5. The method for measuring altitude of meter-wave MIMO radar under complex terrain conditions according to claim 1, characterized in that: The specific operation of the generalized MUSIC algorithm in step S203 is: perform eigenvalue decomposition on the covariance matrix of the complex terrain received data to obtain the noise subspace E n , the terrain-adaptive generalized MUSIC spectrum peak search formula is further expressed as The angle estimate corresponding to the spectrum peak is the target elevation angle.

6. The method for measuring altitude of meter-wave MIMO radar under complex terrain conditions according to claim 5, characterized in that: The specific operation of the maximum likelihood estimation algorithm in step S203 is: scout the terrain to obtain the terrain inclination parameter, then the maximum likelihood estimation value of the target elevation angle, that is, the target elevation angle is Where P A(θ) is the projection matrix formed by projecting the column vectors onto the steering vector matrix A(θ), P A(θ) =A(θ)[A H (θ) A(θ)] -1 A H (θ) (28).

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