Radar height estimation method based on forward-looking squint SAR echo signal

Abstract

The present invention discloses a radar altitude estimation method based on forward-looking squint SAR echo signals, comprising the following steps: acquiring forward-looking squint SAR echo signals and performing range-direction pulse compression; performing frequency-domain range-direction segmentation on the pulse compression signals; transforming the range-direction sub-band signals back into the time domain; estimating the first baseband Doppler frequency of range unit data in the range-azimuth data in the time domain using a time-domain correlation method; resolving fuzzy numbers based on the first baseband Doppler frequency; performing time-domain range-direction segmentation on the pulse compression signals; estimating the second baseband Doppler frequency of the range-direction sub-block signals using a time-domain correlation method; and inferring the Doppler center frequency based on the second baseband Doppler frequency and the fuzzy numbers; calculating the radar altitude based on the Doppler center frequency and slant range by fitting a straight line; and determining a final estimated radar altitude based on the radar altitudes resolved for each range-direction sub-block signal. The present invention achieves accurate radar altitude estimation for high-speed platforms.

Description

Technical Field

[0001] The present invention belongs to the field of radar technology, and in particular relates to a radar height estimation method based on a forward-looking squint SAR (Synthetic Aperture Radar) echo signal. Background Art

[0002] In recent years, hypersonic vehicles (HSVs) have gained widespread popularity worldwide due to their superior maneuverability. These vehicles, operating in close space between 20 and 100 kilometers above Earth, leverage their speed to rapidly reach their target areas and provide superior ground and ocean information. These vehicles integrate new technologies from numerous aerospace disciplines and represent a significant future trend in the field.

[0003] Synthetic aperture radar (SAR) detection technology is one of the active detection methods for high-speed platforms. Its observation performance directly determines the information acquisition capabilities of the flight platform. Radar altitude information can be used to compensate for flight platform motion errors, so radar altitude estimation is very important for high-speed platforms.

[0004] In the prior art, the paper "Estimation of Aircraft Altitude Based on Squint Mode SAR Data", IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 1, pp. 135-139, Jan. 2015, proposes a relative altitude estimator (RAE) based on Doppler center variation. This method observes how the Doppler center of a SAR echo changes with distance, intercepts echo data from multiple range cells to estimate the corresponding Doppler center, and then performs a straight line fit using the reciprocal of the square of the slant range as the independent variable and the square of the Doppler center as the dependent variable. The radar altitude is then calculated by substituting the linear fitting coefficients into the linear fitting coefficients.

[0005] However, due to the weight and volume constraints of high-speed platforms, the inertial navigation equipment they can carry often suffers from insufficient measurement accuracy and a data update rate far lower than the SAR data acquisition rate, resulting in large inertial navigation errors. Estimating the baseband frequency of the Doppler center based on echo data requires deambiguation. Traditional Doppler center deambiguation requires the coarse Doppler center frequency calculated from the initial inertial navigation parameters. However, due to the presence of large inertial navigation errors, the estimated Doppler center ambiguity number deviates from the theoretical value and cannot be used for subsequent Doppler center estimation. Summary of the Invention

[0006] In order to solve the above problems existing in the prior art, the present invention provides a radar height estimation method based on forward-looking SAR echo signals.

[0007] The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0008] A radar height estimation method based on a forward-looking squint SAR echo signal, comprising:

[0009] Acquire a forward squint SAR echo signal, and perform range-direction pulse compression on the forward squint SAR echo signal to obtain a pulse compression signal;

[0010] Performing frequency domain range-wise segmentation on the pulse pressure signal to obtain a plurality of range-wise sub-band signals;

[0011] Convert the multiple range sub-band signals back to the time domain to obtain range-azimuth data in the time domain;

[0012] The method further comprises estimating corresponding first baseband Doppler frequencies for a plurality of range unit data in the range-azimuth data in the time domain using a time domain correlation method; wherein the plurality of range unit data are obtained by transforming a plurality of target range sub-band signals back to the time domain; and the frequencies of the plurality of target range sub-band signals include at least one set of symmetrical frequencies close to and centered around a radar carrier center frequency.

[0013] Resolving ambiguity based on the estimated first baseband Doppler frequency;

[0014] Performing time domain range division on the pulse pressure signal to obtain a plurality of range sub-block signals;

[0015] For each range sub-block signal, the second baseband Doppler frequency corresponding to each range gate of the range sub-block signal is estimated using the time domain correlation method, and the Doppler center frequency corresponding to each range gate is calculated using the fuzzy number according to the second baseband Doppler frequency; according to the calculated Doppler center frequency and the slant range corresponding to each range gate, the linear fitting fdc is used to calculate the Doppler center frequency corresponding to each range gate. 2 =a1+a2 / R 2 To solve the radar altitude Where R represents the slant range, fdc represents the second baseband Doppler frequency, a1 represents the intercept of the straight line, and a2 represents the slope of the straight line.

[0016] The final estimated radar altitude is determined according to the radar altitudes calculated for each range sub-block signal.

[0017] Optionally, resolving an ambiguity number according to the estimated first baseband Doppler frequency includes:

[0018] grouping the estimated first baseband Doppler frequencies according to the frequency symmetry relationship of the multiple target range sub-band signals to obtain multiple groups of first baseband Doppler frequencies;

[0019] A fuzzy number is obtained by solving the simultaneous equations for each set of first baseband Doppler frequencies;

[0020] The multiple fuzzy numbers obtained are averaged to obtain the final fuzzy number;

[0021] Wherein, the equation group is:

[0022]

[0023] Among them, fdc_base1 and fdc_base2 are a set of first baseband Doppler frequencies. The estimated distance unit data of fdc_base1 is the frequency f c -f Δ The target distance is obtained by transforming the sub-band signal back to the time domain, and it is estimated that the distance unit data of fdc_base2 is obtained by transforming the frequency f c +f Δ The target distance is transformed back to the time domain by sub-band signal, f Δ Indicates the target range sub-band signal relative to the radar carrier center frequency f c The frequency offset; v is the flight speed of the flight platform where the radar is located, θ is the beam squint angle, c is the speed of light, B is the bandwidth of the radar transmission signal, PRF is the radar pulse repetition frequency, N amb is a fuzzy number obtained by solving the system of equations.

[0024] Optionally, averaging the multiple fuzzy numbers to obtain the final solved fuzzy number includes: averaging the multiple fuzzy numbers and then rounding the average to obtain the final solved fuzzy number.

[0025] Optionally, the calculating the Doppler center frequency corresponding to each range gate using the fuzzy number according to the second baseband Doppler frequency includes:

[0026] fdc n =fdc_base n +Na·PRF;

[0027] Among them, fdc_base n represents the second baseband Doppler frequency corresponding to the nth range gate, Na represents the fuzzy number to be solved, and fdc n It represents the Doppler center frequency corresponding to the nth range gate, and PRF is the radar pulse repetition frequency.

[0028] Optionally, determining a final estimated radar altitude according to radar altitudes calculated for respective range sub-block signals includes:

[0029] The radar altitudes calculated for each range sub-block signal are averaged to obtain the final estimated radar altitude.

[0030] Optionally, the calculated Doppler center frequency and the slant distance corresponding to the range sub-block signal are obtained by fitting a straight line fdc 2 =a1+a2 / R 2 To solve the radar altitude include:

[0031] According to the calculated Doppler center frequency and the slant range corresponding to each range gate, the least squares method is used to fit the straight line fdc 2 =a1+a2 / R 2 To solve the radar altitude

[0032] Optionally, the flying platform includes a high speed platform HSV.

[0033] In the radar altitude estimation method based on forward squint SAR echo signals provided by the present invention, range-direction pulse compression is performed on the forward squint SAR echo signals to obtain a pulse compression signal; the pulse compression signal is subjected to frequency-domain range-direction segmentation to obtain a plurality of range-direction sub-band signals; the plurality of range-direction sub-band signals are transformed back into the time domain to obtain range-azimuth data in the time domain; a time-domain correlation method is used to estimate the corresponding first baseband Doppler frequencies of a plurality of range unit data in the range-azimuth data in the time domain; an accurate fuzzy number is solved based on the estimated first baseband Doppler frequency, and an accurate Doppler center frequency is calculated using the fuzzy number, thereby calculating an accurate radar altitude based on the calculated Doppler center frequency and the slant range corresponding to each range gate by fitting a straight line.

[0034] The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a flow chart of a radar height estimation method based on forward-looking SAR echo data provided by an embodiment of the present invention;

[0036] Figure 2 This is a simplified flow chart of a radar height estimation method based on forward-looking SAR echo data provided by an embodiment of the present invention;

[0037] Figure 3 This is the geometric relationship diagram of forward squint SAR imaging;

[0038] Figure 4Schematic diagram of frequency domain distance segmentation of a pulse pressure signal in an embodiment of the present invention;

[0039] FIG5( a ) and FIG5 ( b ) show the first baseband Doppler frequency corresponding to each range unit data in simulation experiment 1;

[0040] Figure 6 The changing trend of the Doppler center corresponding to each range unit in the 5th range sub-block signal in simulation experiment 1 is shown;

[0041] Figure 7 The simulation experiment 1 shows the inverse of each distance squared 1 / R 2 is the independent variable, and the corresponding Doppler center square fdc 2 The straight line fitted to the dependent variable;

[0042] Figures 8(a) and 8(b) show the changing trends of the Doppler center corresponding to each range unit in the 5th range sub-block signal in simulation experiment 2;

[0043] Figure 9 The changing trend of the Doppler center corresponding to each range unit in the 5th range sub-block signal in simulation experiment 2 is shown;

[0044] Figure 10 The simulation experiment 2 shows the reciprocal of each distance squared 1 / R 2 is the independent variable, and the corresponding Doppler center square fdc 2 The straight line fitted to the dependent variable. DETAILED DESCRIPTION

[0045] The present invention will be further described in detail below with reference to specific examples, but the embodiments of the present invention are not limited thereto.

[0046] Considering the impact of large inertial guidance errors and ultra-high-speed motion on echo Doppler center estimation on high-speed platforms, an embodiment of the present invention provides a radar altitude estimation method based on forward-looking SAR echo data to accurately estimate the radar altitude of a high-speed platform. The technical concept of this method is to perform deambiguation analysis on the target echo after pulse compression to obtain an accurate fuzzy number. Then, by dividing the echo signal into range blocks, conjugate multiplication and summing and averaging each range sub-block signal (i.e., time-domain correlation method) is performed to obtain the baseband Doppler frequency. The accurate fuzzy number is substituted into the baseband Doppler center to infer the corresponding Doppler center. A straight line fit is performed using the inverse of the square of the skew moment as the independent variable and the square of the corresponding Doppler center as the dependent variable. The radar altitude is estimated based on the slope and intercept coefficient of the fitted line.

[0047] The radar height estimation method based on forward-looking SAR echo data provided by the embodiment of the present invention is described in detail below. Figure 1 and Figure 2 As shown, the method includes the following steps:

[0048] S10: Acquire a forward squint SAR echo signal, and perform range-direction pulse compression on the forward squint SAR echo signal to obtain a pulse compression signal.

[0049] Specifically, Figure 3 The figure shows the geometric relationship diagram of forward squint SAR imaging, where the sub-satellite point of the radar synthetic aperture center is the origin of the coordinate system, R represents the distance between the point target P and the synthetic aperture center, θ is the beam squint angle, α is the horizontal azimuth angle, H is the radar altitude, and v is the flight speed of the flight platform.

[0050] Assuming that the radar is located at the center of the synthetic aperture at slow time t = 0, the instantaneous distance between the radar and the target P is expressed as:

[0051]

[0052] Where R(t) represents the instantaneous distance from the radar to the target P at time t.

[0053] After R(t) is demodulated to baseband, the echo signal of the point target P can be expressed as:

[0054]

[0055] Where σ is the target scattering coefficient, τ is the fast time, t is the slow time, c is the speed of light, T p is the pulse width, T a is the total azimuth time, γ is the modulation frequency, j represents an imaginary number, is the signal propagation two-way delay RTTD, f c is the radar carrier center frequency; u in the above formula Middle reference In the above formula The middle refers to exp[] represents an exponential function with the natural constant e as the base; s(τ,t) represents the echo signal.

[0056] Compress the wide pulse into a narrow pulse and perform pulse compression on the echo signal. Assume that the matched filter is:

[0057]

[0058] Here, h(τ) represents a matched filter.

[0059] The echo signal s(τ,t) is convolved with the matched filter in the time domain to obtain the output signal after pulse compression, referred to as the pulse compression signal, which is expressed as:

[0060]

[0061] Where B = γ·T p is the bandwidth of the radar transmission signal, u here refers to the sinc function Input parameter, s out (τ, t) represents the pulse pressure signal.

[0062] S20: performing frequency domain range-wise segmentation on the pulse pressure signal to obtain a plurality of range-wise sub-band signals.

[0063] Specifically, the pulse compression signal is divided into range blocks, and then each range sub-block is Fourier transformed, thereby transforming from the range time domain-azimuth time domain to the range frequency-azimuth time domain; the entire target echo in the range frequency-azimuth time domain is evenly cut into multiple segments along the range frequency to obtain multiple range sub-band signals.

[0064] by Figure 4 As an example, the rectangular area is the entire target echo in the range frequency-azimuth time domain. The pulse pressure signal is divided into blocks in the frequency domain and the range direction, and the result is f c The frequencies of the two range-direction sub-band signals are as follows: as well as

[0065] S30: transform the multiple range sub-band signals back to the time domain to obtain range-azimuth data in the time domain.

[0066] Specifically, each range-azimuth sub-band signal is subjected to inverse Fourier transform to return to the time domain, and these signals transformed back to the time domain together constitute range-azimuth data in the time domain.

[0067] S40: Estimate corresponding first baseband Doppler frequencies for a plurality of range unit data in the range-azimuth data in the time domain using a time domain correlation method; wherein the plurality of range unit data are obtained by transforming a plurality of target range sub-band signals back to the time domain; and the frequencies of the plurality of target range sub-band signals include at least one set of symmetrical frequencies close to and centered on a radar carrier center frequency.

[0068] Still Figure 4 For example, and is a set of range sub-band signals, and they are all at a distance from the radar carrier center frequency f c Closer, so and These are all target range sub-band signals. By converting them back to time-domain signals, the corresponding first baseband Doppler frequencies are estimated using the time-domain correlation method using the range cell data. This yields two first baseband Doppler frequencies. It should be noted that the number of target range sub-band signals can be set based on actual circumstances, such as 32 or 64. This example uses only two target range sub-band signals.

[0069] S50: Resolving ambiguity numbers according to the estimated first baseband Doppler frequency.

[0070] Specifically, step S50 includes the following sub-steps:

[0071] (1) grouping the estimated first baseband Doppler frequencies according to the frequency symmetry relationship of the multiple target range sub-band signals to obtain multiple groups of first baseband Doppler frequencies;

[0072] Still Figure 4 For example, according to and The frequency symmetry relationship will be from the target distance to the sub-band signal The first baseband Doppler frequency estimated by the range unit obtained by transforming back to the time domain and the sub-band signal from the target range The first baseband Doppler frequency estimated by the range unit obtained by transforming back to the time domain is divided into a group.

[0073] (2) obtaining a fuzzy number based on each set of simultaneous equations for the first baseband Doppler frequency and solving the equations;

[0074] Among them, the equation system is:

[0075]

[0076] Eliminate the unknown number sinθ and get the fuzzy number N amb The expression is:

[0077]

[0078] Among them, fdc_base1 and fdc_base2 are a set of first baseband Doppler frequencies. The estimated distance unit data of fdc_base1 is the frequency f c -f Δ The target distance is obtained by transforming the sub-band signal back to the time domain, and it is estimated that the distance unit data of fdc_base2 is obtained by transforming the frequency f c +f Δ The target distance is transformed back to the time domain by sub-band signal, f ΔIt represents the frequency offset of the target range sub-band signal relative to the center frequency of the radar carrier; PRF is the radar pulse repetition frequency.

[0079] It can be understood that, assuming that there are m target range sub-band signals, m-1 fuzzy numbers can be obtained in step (2).

[0080] (3) Average the multiple fuzzy numbers obtained to obtain the final fuzzy number.

[0081] Alternatively, the multiple fuzzy numbers obtained may be further averaged and then integerized (eg, rounded off) to obtain the final fuzzy number.

[0082] S60: Perform time-domain range-wise block division on the pulse pressure signal to obtain a plurality of range-wise sub-block signals.

[0083] S70: For each range sub-block signal, use the time domain correlation method to estimate the second baseband Doppler frequency corresponding to each range gate of the range sub-block signal, and use the fuzzy number to infer the Doppler center frequency corresponding to each range gate based on the second baseband Doppler frequency; according to the inferred Doppler center frequency and the slant range corresponding to each range gate, calculate the Doppler center frequency corresponding to each range gate by fitting the straight line fdc 2 =a1+a2 / R 2 To solve the radar altitude

[0084] Wherein, R represents the slant range, fdc represents the second baseband Doppler frequency, a1 represents the intercept of the straight line, and a2 represents the slope of the straight line.

[0085] In step S70, the second baseband Doppler frequency corresponding to each range gate of the range sub-block signal is estimated using a time domain correlation method, including: performing conjugate multiplication and summing and averaging the data under each range gate of the range sub-block signal (i.e., the time domain correlation method) to obtain the second baseband Doppler frequency.

[0086] Since the SAR pulse repetition frequency (PRF) limits the maximum acceptable Doppler frequency in azimuth, only the [-PRF / 2, PRF / 2] interval can be observed. When the Doppler center is large, the echo signal can only obtain the baseband Doppler frequency using the time domain correlation method. Therefore, the Doppler center frequency consists of two parts: the baseband Doppler frequency and the Doppler ambiguity:

[0087] fdc=fdc_base+N·PRF

[0088] Where fdc_base is the baseband Doppler frequency and N is the fuzzy number.

[0089] Therefore, in the embodiment of the present invention, for each range sub-block signal, the second baseband Doppler frequency corresponding to each range gate of the range sub-block signal is estimated using a time domain correlation method, including:

[0090] fdc n =fdc_base n +Na·PRF;

[0091] Among them, fdc_base n represents the second baseband Doppler frequency corresponding to the nth range gate, Na represents the fuzzy number to be solved, and fdc n It represents the Doppler center frequency corresponding to the nth range gate, and PRF is the radar pulse repetition frequency.

[0092] In the embodiment of the present invention, according to the calculated Doppler center frequency and the slant range corresponding to each range gate, the fitting straight line fdc 2 =a1+a2 / R 2 To solve the radar altitude The implementation principle is analyzed as follows:

[0093] Reference Figure 3 Assuming that the radar platform is flying level, the Doppler center fdc of the forward squint SAR echo is expressed as: Where λ is the radar operating wavelength.

[0094] in accordance with Figure 3 The beam squint angle can be expressed by the horizontal azimuth angle α and the height H:

[0095]

[0096] Substituting into the sinθ expression, the Doppler center frequency fdc can be rewritten as:

[0097]

[0098] Doppler center frequency fdc 2 The square of can be expressed as:

[0099]

[0100] make We can get:

[0101] fdc 2 =a1+a2 / R 2 ;

[0102] It can be seen that the square of the Doppler center frequency fdc 2 With the square of the slope distance R 2 Therefore, the square of multiple slope distances R2 The reciprocal of is the independent variable, and the corresponding square of the Doppler center is fdc 2 Using the linear fit as the dependent variable, we can get the intercept a1 and slope a2 of the fitted line to calculate the radar height.

[0103] In practical applications, according to the calculated Doppler center frequency and the slant range corresponding to each range gate, the straight line fdc is fitted. 2 =a1+a2 / R 2 To solve the radar altitude It can include: fitting the straight line fdc using the least squares method based on the calculated Doppler center frequency and the slant range corresponding to each range gate 2 =a1+a2 / R 2 To solve the radar altitude

[0104] Specifically, the process of fitting a straight line using the least squares method is expressed in a matrix. Let F be the Doppler center frequency matrix, G be the slant range matrix, and θ be the parameter to be estimated. Then:

[0105] F=[fdc1 2 fdc2 2 ... fdc n 2 ] T ,

[0106]

[0107] θ=[a1 a2] T ;

[0108] Among them, R n Indicates the slant range corresponding to the nth range gate.

[0109] Based on the least squares solution criterion, the estimate of the θ matrix is obtained:

[0110]

[0111] The intercept coefficient of the fitted straight line and the slope coefficient Calculate the estimated radar altitude

[0112]

[0113] Of course, the algorithm for fitting a straight line is not limited to the least squares method. For example, algorithms such as interpolation can also be used.

[0114] S80: Determine a final estimated radar altitude according to the radar altitudes calculated for each range sub-block signal.

[0115] Here, considering the limited range of fuzzy numbers, the radar altitudes calculated for each range sub-block signal can be averaged to obtain the final estimated radar altitude. Alternatively, a threshold can be used to filter out outliers in the radar altitudes calculated for each range sub-block signal, and then the remaining radar altitudes can be averaged to obtain the final estimated radar altitude.

[0116] It can be understood that determining the final estimated radar altitude based on the radar altitude calculated for each range sub-block signal can reduce the impact of extreme data on the altitude result and improve the altitude estimation accuracy.

[0117] It is worth mentioning that the height measured by traditional instruments is only the height difference between the radar and the radar subsatellite point, while the radar height obtained by the embodiment of the present invention is the relative height between the radar and the imaging area.

[0118] In a radar altitude estimation method based on forward-looking squint SAR echo signals provided by an embodiment of the present invention, the forward-looking squint SAR echo signal is pulse compressed in the range direction to obtain a pulse compression signal; the pulse compression signal is frequency-domain segmented in the range direction to obtain multiple range sub-band signals; the multiple range sub-band signals are transformed back to the time domain to obtain time-domain range-azimuth data; the corresponding first baseband Doppler frequencies are estimated using a time-domain correlation method for multiple range unit data in the time-domain range-azimuth data; an accurate fuzzy number is resolved based on the estimated first baseband Doppler frequency, and the accurate Doppler center frequency is calculated using the fuzzy number. Based on the calculated Doppler center frequency and the slant range corresponding to each range gate, the accurate radar altitude is calculated by fitting a straight line. Furthermore, the embodiment of the present invention takes into account the system and payload limitations of the hypersonic flight platform, reduces the need for additional measurement equipment, and can estimate the platform altitude based on the echo signal. Therefore, the implementation of the embodiment of the present invention does not require the use of initial inertial navigation parameters, and the existence of large inertial navigation errors has no impact on the present invention.

[0119] The beneficial effects of the embodiments of the present invention are further illustrated below through simulation experiments.

[0120] Experiment 1.

[0121] 1. Simulation conditions: Set the high-speed flight platform SAR system parameters as shown in Table 1.

[0122] Table 1 SAR system parameters of high-speed flight platform

[0123] Band Ku Platform height 50km Scene center distance 120km Platform speed 4083m / s Front oblique angle 5° Pulse Width 15us bandwidth 50MHz Sampling rate 60MHz Pulse repetition frequency 5kHz

[0124] The simulation experiment compares the fuzzy number and height estimation results calculated by the embodiment of the present invention with those by the RAE method mentioned in the background art under the condition of large inertial navigation error.

[0125] 2. Simulation content:

[0126] In the forward squint scenario, the forward squint angle is 5° and the inertial guidance error is 5 km. Based on the range sub-band signal, the ambiguity number is resolved and the time domain correlation method is used to estimate the first baseband Doppler frequency for the 96 range unit data in the middle of the range time domain. The first baseband Doppler frequency corresponding to each range unit data is shown in Figure 5(a) and Figure 5(b). The corresponding frequency in Figure 5(a) is lower than f c The range sub-band signal of Figure 5(b) corresponds to a frequency higher than f c The range sub-band signal.

[0127] Substitute these 96 sets of baseband Doppler frequencies into N amb In the expression of , 96 N are solved. amb The fuzzy number is obtained by taking the average and rounding it off. It is compared with the fuzzy number estimation value of the RAE algorithm. The comparison results are shown in Table 2.

[0128] Table 2 Comparison results of fuzzy numbers for 5° front strabismus

[0129] Theoretical value RAE algorithm The present invention fuzzy numbers 84 82 84

[0130] It can be seen that the error between the fuzzy number estimated by the RAE algorithm and the theoretical value is -2, and the fuzzy number estimated by the embodiment of the present invention is consistent with the theoretical value.

[0131] Based on the derived relationship between the Doppler center frequency and the slant range, the pulse compression signal is divided into five range sub-block signals in the simulation experiment. The Doppler center frequency estimation result of the fifth range sub-block signal is taken as an example. Figure 6 The changing trend of the Doppler center corresponding to each range unit in the sub-block is shown. Figure 7 Shows the inverse of the square of each distance 1 / R 2 is the independent variable, and the corresponding Doppler center square fdc 2 As shown in the figure, the RAE algorithm is significantly different from the theoretical value, while the embodiment of the present invention is consistent with the theoretical value.

[0132] Table 3 shows a comparison of the height estimation errors for each sub-block using the RAE algorithm and the embodiment of the present invention. After averaging, the final error of the RAE algorithm is 519.84 m, while the final error of the embodiment of the present invention is 19.43 m. Compared with the RAE algorithm, the embodiment of the present invention has better estimation accuracy under conditions of large inertial navigation errors at hypersonic speeds.

[0133] Table 3 SAR height error at 5° forward squint

[0134] Sub-block number 1 2 3 4 5 RAE algorithm 530.77 516.19 518.31 516.42 517.52 The present invention 30.52 15.91 17.91 15.91 16.89

[0135] Experiment 2.

[0136] 1. Simulation conditions: Set the high-speed flight platform SAR system parameters as shown in Table 4.

[0137] Table 4 High-speed flight platform SAR system parameters

[0138] Band Ku Platform height 50km Scene center distance 120km Platform speed 3743m / s Front oblique angle 8° Pulse Width 15us bandwidth 50MHz Sampling rate 60MHz Pulse repetition frequency 5kHz

[0139] 2. Simulation content:

[0140] In the forward squint scenario, the forward squint angle is set to 8° and the inertial guidance error is 7 km. The ambiguity is resolved based on the range sub-band signal. The time domain correlation method is used to estimate the baseband Doppler frequency for the 96 range cells in the middle of the range time domain. The baseband Doppler frequencies corresponding to each range cell are shown in Figures 8(a) and 8(b). The corresponding frequencies in Figure 8(a) are lower than f c The range sub-band signal of Figure 8(b) corresponds to a frequency higher than f c The range sub-band signal.

[0141] Substitute these 96 sets of baseband Doppler frequencies into N amb In the expression of , 96 N are solved. amb The fuzzy number estimation value is averaged and rounded off, and then compared with the fuzzy number estimation value of the RAE algorithm. The comparison results are shown in Table 5. The error between the fuzzy number estimated by the RAE algorithm and the theoretical value is -2, while the fuzzy number estimated by the embodiment of the present invention is consistent with the theoretical value.

[0142] Table 5 Comparison results of fuzzy numbers for 8° front strabismus

[0143] Theoretical value RAE algorithm The present invention fuzzy numbers 76 74 76

[0144] The baseband Doppler frequency estimated by the time domain correlation method is substituted into the fuzzy number solved by the equation group to infer the corresponding Doppler center. According to the changing relationship between the Doppler center and the slant range, the height is solved by fitting a straight line. The pulse pressure signal is divided into 5 sub-block signals in the distance direction. The Doppler center estimation result of the Doppler center of the signal of the 5th sub-block is taken as an example. Figure 9 It shows the changing trend of Doppler center with each distance unit. Figure 10 The figure shows the variation of the square of the Doppler center within a sub-block with the inverse of the square of the distance. As can be seen from the comparison, the RAE algorithm differs greatly from the theoretical value, while the embodiment of the present invention is consistent with the theoretical value.

[0145] Table 6 shows a comparison of the height estimation errors for each sub-block using the RAE algorithm and the embodiment of the present invention. After averaging, the final error for the RAE algorithm is 577.04 m, while the final error for the embodiment of the present invention is 27.05 m. Compared with the RAE algorithm, the embodiment of the present invention has better estimation accuracy under conditions of large inertial navigation errors at hypersonic speeds.

[0146] Table 6 SAR height error at 8° forward squint

[0147] Sub-block number 1 2 3 4 5 RAE algorithm 596.95 578.02 571.02 570.09 569.13 Embodiments of the present invention 47.09 28.15 21.06 20.01 18.94

[0148] The above experimental simulation results show that the radar altitude estimation method based on the forward squint SAR echo signal provided by the embodiment of the present invention can achieve accurate estimation of the radar altitude of a high-speed platform.

[0149] It should be noted that the radar altitude estimation method based on the forward squint SAR echo signal provided by the embodiment of the present invention can achieve accurate radar altitude estimation for both high-speed platforms and low-speed platforms.

[0150] It should be noted that the terms "first," "second," and the like are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0151] In the description of this specification, the reference terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" mean that the specific features or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described can be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification.

[0152] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other variations of the disclosed embodiments by reviewing the drawings and the disclosed content. In the description of the present invention, the word "comprising" does not exclude other steps, "one" or "a" does not exclude multiple situations, and "multiple" means two or more, unless otherwise clearly and specifically limited. In addition, certain measures are recorded in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0153] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, devices (equipment), or computer program products. Therefore, the application can adopt the form of complete hardware embodiment, complete software embodiment, or the embodiment in combination with software and hardware, which are all collectively referred to as "module" or "system" herein. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The computer program is stored / distributed in a suitable medium, provided together with other hardware or as a part of hardware, or other distribution forms can be adopted, such as by the Internet or other wired or wireless telecommunication systems.

[0154] The present application is described with reference to the flowcharts and / or block diagrams of the methods, apparatus (devices) and computer program products of the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0155] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0156] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0157] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A radar height estimation method based on forward-looking squint SAR echo signal, characterized in that: include: Acquire a forward squint SAR echo signal, and perform range-direction pulse compression on the forward squint SAR echo signal to obtain a pulse compression signal; Performing frequency domain range-wise segmentation on the pulse pressure signal to obtain a plurality of range-wise sub-band signals; Convert the multiple range sub-band signals back to the time domain to obtain range-azimuth data in the time domain; The method further comprises estimating corresponding first baseband Doppler frequencies for a plurality of range unit data in the range-azimuth data in the time domain using a time domain correlation method; wherein the plurality of range unit data are obtained by transforming a plurality of target range sub-band signals back to the time domain; and the frequencies of the plurality of target range sub-band signals include at least one set of symmetrical frequencies close to and centered around a radar carrier center frequency. Resolving ambiguity based on the estimated first baseband Doppler frequency; Performing time domain range division on the pulse pressure signal to obtain a plurality of range sub-block signals; For each range sub-block signal, the second baseband Doppler frequency corresponding to each range gate of the range sub-block signal is estimated using the time domain correlation method, and the Doppler center frequency corresponding to each range gate is calculated using the fuzzy number according to the second baseband Doppler frequency; according to the calculated Doppler center frequency and the slant range corresponding to each range gate, the linear fitting fdc is used to calculate the Doppler center frequency corresponding to each range gate. 2 =a1+a2 / R 2 To solve the radar altitude Where R represents the slant range, fdc represents the second baseband Doppler frequency, a1 represents the intercept of the straight line, and a2 represents the slope of the straight line. The final estimated radar altitude is determined according to the radar altitudes calculated for each range sub-block signal.

2. The radar height estimation method based on the forward-looking SAR echo signal according to claim 1, wherein: Resolving ambiguity based on the estimated first baseband Doppler frequency includes: Grouping the estimated first baseband Doppler frequencies according to the frequency symmetry relationship of the multiple target range sub-band signals to obtain multiple groups of first baseband Doppler frequencies; A fuzzy number is obtained by solving the simultaneous equations for each set of first baseband Doppler frequencies; The multiple fuzzy numbers obtained are averaged to obtain the final fuzzy number; Wherein, the equation group is: Among them, fdc_base1 and fdc_base2 are a set of first baseband Doppler frequencies. The estimated distance unit data of fdc_base1 is the frequency f c -f Δ The target distance is obtained by transforming the sub-band signal back to the time domain, and it is estimated that the distance unit data of fdc_base2 is obtained by transforming the frequency f c +f Δ The target distance is transformed back to the time domain by sub-band signal, f Δ Indicates the target range sub-band signal relative to the radar carrier center frequency f c The frequency offset; v is the flight speed of the flight platform where the radar is located, θ is the beam squint angle, c is the speed of light, B is the bandwidth of the radar transmission signal, PRF is the radar pulse repetition frequency, N amb is a fuzzy number obtained by solving the system of equations.

3. The radar height estimation method based on the forward-looking SAR echo signal according to claim 2, wherein: The averaging of the multiple fuzzy numbers to obtain the final solved fuzzy number includes: averaging the multiple fuzzy numbers and then rounding them to obtain the final solved fuzzy number.

4. The radar height estimation method based on the forward-looking SAR echo signal according to claim 1, wherein: The calculating the Doppler center frequency corresponding to each range gate using the fuzzy number according to the second baseband Doppler frequency includes: fdc n =fdc_base n +Na·PRF; Among them, fdc_base n represents the second baseband Doppler frequency corresponding to the nth range gate, Na represents the fuzzy number to be solved, and fdc n It represents the Doppler center frequency corresponding to the nth range gate, and PRF is the radar pulse repetition frequency.

5. The radar height estimation method based on the forward-looking SAR echo signal according to claim 1, wherein: Determining a final estimated radar altitude according to the radar altitudes calculated for each range sub-block signal includes: The radar altitudes calculated for each range sub-block signal are averaged to obtain the final estimated radar altitude.

6. The radar height estimation method based on the forward-looking SAR echo signal according to claim 1, wherein: The calculated Doppler center frequency and the slant range corresponding to the range sub-block signal are obtained by fitting a straight line fdc 2 =a1+a2 / R 2 To solve the radar altitude include: According to the calculated Doppler center frequency and the slant range corresponding to each range gate, the least squares method is used to fit the straight line fdc 2 =a1+a2 / R 2 To solve the radar altitude 7. The radar height estimation method based on forward-looking squint SAR echo signal according to any one of claims 1 to 6, characterized in that: The flying platform includes a high speed platform HSV.

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