Sar motion parameter estimation method based on time of arrival and direction of arrival accurate measurement

Abstract

The application discloses a SAR motion parameter estimation method based on accurate measurement of time of arrival and direction of arrival, which comprises the following steps: reading N LFM direction of arrival alpha n and corresponding measurement value of time of arrival t n , performing cubic polynomial fitting on the line of sight angle alpha n by using a least square method to smooth measurement error; performing quadratic polynomial fitting on the time of arrival t n by using a least square method to obtain a linear term coefficient p1 and a quadratic term coefficient p2; obtaining a radar pulse repetition interval T by using a statistical pulse time of arrival difference; updating a detection pulse serial number n; solving a radar initial distance r0; and solving a radar flight speed v and a flight direction beta by using the initial distance r0, the direction of arrival alpha n and the time of arrival t n . The application has the characteristic that a signal waveform of a SAR emission is synthesized with an LFM pulse, accurate estimation of SAR motion parameters is realized, the variation rate parameter of the line of sight angle is avoided, and the robustness of the algorithm is improved and the requirement for the direction finding accuracy is reduced.

Description

Technical Field

[0001] This invention relates to radar countermeasures, electronic reconnaissance, and passive positioning technologies, specifically to a method for estimating SAR motion parameters based on accurate measurements of arrival time and direction of arrival. Background Technology

[0002] Unlike traditional radar, which primarily functions to detect targets and measure their position and motion parameters, synthetic aperture radar (SAR) is mainly used for two-dimensional high-resolution imaging of large-area scenes. Operating in the microwave band, SAR imaging offers all-weather, all-day operation and strong penetration, compensating for the shortcomings of existing optical imaging. With technological advancements, SAR devices are becoming increasingly smaller and lighter, leading to the increasing use of miniaturized unmanned aerial vehicles (UAVs) as their mounting platforms. All of this makes SAR applications not only significantly less expensive but also increasingly convenient.

[0003] SAR achieves high-resolution imaging based on the principle of two-dimensional pulse compression, that is, transmitting linear frequency modulated (LFM) pulses to achieve high resolution in the range direction, possessing extremely high signal processing gain, which is the key reason why traditional radar countermeasures are ineffective. Since SAR relies on the relative motion between itself and the scene to obtain the Doppler modulation of the echo in the azimuth direction, SAR reconnaissance requires not only parameters such as the carrier frequency, pulse width, arrival time, direction of arrival, and amplitude of the radar transmitted signal, but also flight parameters such as the radar's flight speed, flight direction, and range.

[0004] For the above parameters, traditional SAR motion parameter estimation methods mainly rely on the principle of particle kinematics. They obtain radar parameters such as range, flight direction, and flight speed by estimating the Doppler frequency modulation slope between multiple received pulses (azimuth direction) and accurately measuring the pulse arrival direction, i.e., the radar line-of-sight angle.

[0005] Traditional radar motion parameter estimation geometric relationship models, such as Figure 1 As shown, Figure 1 In this system, a rectangular coordinate system XOY is established with the jamming system's receiving antenna as the origin, and X coincides with the baseline of the direction-finding system's phase interferometer; the radar moves in a uniform linear motion at a velocity v, with a heading of β (the angle between the flight direction and the Y-axis); v x v y These are the components of the radar's flight speed v in the X and Y directions, respectively; α is the line-of-sight angle (direction of arrival) of the jamming system to the radar, defined with the Y-axis as zero and clockwise as positive; r is the distance between the radar and the jamming system, and r0 is the distance between the radar and the jamming system at time t0.

[0006] Let λ be the wavelength of the received radar pulse signal, and f be the Doppler frequency change rate, which is also the Doppler modulation slope. rjThe viewing angle α at different times, and the rate of change of the viewing angle obtained from the viewing angle. Based on the principles of particle kinematics, the distance between the radar and the receiving antenna can be calculated as follows:

[0007]

[0008] Let t n The line-of-sight angle measured at time α n n = 0, 1, 2, ..., N. t0 = 0, which is the moment when the jamming system receives the first radar pulse (the moment when the edge of the radar antenna beam sweeps across the jamming system). The radar's position at time t0 is (x0, y0). Then by Figure 1 The geometric model shown can be obtained

[0009]

[0010] From the above equation, we can further obtain

[0011]

[0012] Solving equation (4) using the least squares method yields the components of the flight velocity v in the X and Y directions. x v y .

[0013] Using v x v y Then the radar flight speed v can be obtained as

[0014]

[0015] The direction of flight β is

[0016]

[0017] The aforementioned existing technologies have two main drawbacks:

[0018] 1) In reality, the distance between the radar and the jamming system is relatively far. The radar moves in a straight line and its flight speed is limited compared to the distance (speed is a few hundred meters per second or lower, distance is a few kilometers or more), which makes the rate of change of the line of sight angle very small. Thus, as can be seen from equation (1), even a small error in the rate of change of the line of sight angle will seriously affect the accuracy of distance estimation, and thus affect the accuracy of estimation of other parameters.

[0019] 2) Traditional methods require estimating the Doppler modulation slope f of the received pulse. rjThe accuracy of Doppler frequency modulation slope estimation is related to the measurement accuracy of the pulse arrival time (the moment when the pulse leading edge exceeds the detection threshold). However, traditional pulse arrival time measurement generally uses a threshold comparison method based on digital counting, which has large measurement errors and thus seriously affects the estimation accuracy of Doppler frequency modulation slope. Summary of the Invention

[0020] Purpose of the Invention: The purpose of this invention is to address the shortcomings of existing technologies and provide a SAR motion parameter estimation method based on accurate measurement of arrival time and direction of arrival. This invention leverages the characteristic that most of the signal waveforms transmitted by synthetic aperture radar (SAR) are LFM pulses with a large time-bandwidth product, thereby achieving accurate estimation of SAR motion parameters. By avoiding the use of the line-of-sight angle change rate parameter, the robustness of the algorithm can be improved and the requirements for direction-finding accuracy can be reduced. It is particularly suitable for implementation in modern digital signal processing systems based on DSP+FPGA.

[0021] Technical solution: This invention provides a method for estimating SAR motion parameters based on accurate measurements of arrival time and direction of arrival, comprising the following steps:

[0022] Step (1): Read N LFM arrival directions and corresponding arrival times, and denot them as α. n and t n n is the pulse number, n = 0, 1, 2, ..., N-1; the direction of arrival refers to the line-of-sight angle of the jamming system to the radar;

[0023] Step (2): Use the least squares method to measure the line-of-sight angle α. n Perform cubic polynomial fitting to smooth out the error in the measured values;

[0024] Step (3): Use the least squares method to calculate the arrival time t. n Perform a quadratic polynomial fitting to smooth out the error of the measured values, and then obtain the coefficients p1 of the first term and p2 of the quadratic term.

[0025] Step (4): Since the distance traveled by the radar within one pulse repetition period T is very small, the radar pulse repetition interval T is obtained by using the statistical pulse arrival time difference.

[0026] First, calculate b n =a n+1 -a n ,0≤n <N-1

[0027] Then, the arrival time difference b between adjacent pulses is calculated. n The histogram, the b corresponding to the peak in the histogram n The value is taken as T;

[0028] Among them, a n+1This refers to the arrival time t n+1 The measured line-of-sight angle;

[0029] For example, if the radar pulse repetition interval T is 1ms and the radar flight speed v is 100m / s, then the time difference between adjacent pulses and T will not exceed vT / c = 0.333ns.

[0030] Step (5): To prevent pulse loss from causing pulse sequence number errors, the detected pulse sequence number n needs to be updated.

[0031] Where, round(·) is the rounding function; if there is no pulse loss between adjacent pulses, then... Conversely, if there is pulse loss between adjacent pulses, then round(b) n / T)>1;

[0032] For example, if the radar emits 100 pulses, but the detection system misses the 50th pulse and only detects 99 pulses, then the 50th pulse received by the detection system is actually the 51st pulse emitted by the radar. In this case, it is necessary to restore the number of the detected 50th pulse to the correct 51 based on the measured pulse arrival time information.

[0033] Step (6): Solve for the initial radar range r0;

[0034] Step (7): Using the radar initial range r0 and arrival direction α obtained above... n and arrival time t n Solve for the radar's flight speed v and flight direction β.

[0035] Furthermore, the specific method for solving the radar initial range r0 in step (6) is as follows:

[0036]

[0037] In the above formula,

[0038]

[0039]

[0040] According to u n v n w n h n and q n To solve for r0;

[0041] γ n =α n -α0, where α0 is the line-of-sight angle of the pulse arriving at time t0, and c is the speed of light; un v n w n w n h n q n and γ n All of these are intermediate calculations.

[0042] Furthermore, the specific method for obtaining the radar flight speed v and flight direction β in step (7) is as follows:

[0043] First, using the radar's initial range r0 and direction of arrival α... n and arrival time t n Solve for the components of the flight velocity v in the X and Y directions. x v y ;

[0044] Then, using v x v y Then the radar flight speed v can be obtained as:

[0045] The direction of flight β is:

[0046] Beneficial effects: This invention leverages the characteristic that the signal waveforms transmitted by synthetic aperture radar (SAR) are mostly LFM pulses with a large time-bandwidth product. Based on the pulse arrival time and direction-of-arrival information, it achieves accurate estimation of SAR motion parameters, significantly reducing the requirements for direction-finding accuracy. It is suitable for implementation in modern digital signal processing systems based on DSP+FPGA. Specifically, it includes the following advantages:

[0047] (1) This invention fully utilizes the characteristic that SAR transmits LFM pulses and can accurately measure the pulse arrival time based on frequency measurement. Combined with pulse arrival direction information, it can accurately estimate radar motion parameters in a short time.

[0048] (2) Since the present invention does not need to utilize the information on the rate of change of the line of sight angle, the measurement accuracy requirement for the pulse arrival direction is much lower than that of the traditional method.

[0049] (3) Since the measurement accuracy requirement of the pulse arrival direction is much lower than that of the traditional method, the radar flight time (corresponding flight distance) required to achieve radar motion parameter estimation with the same accuracy is less than that of the traditional method under the same conditions.

[0050] (4) The present invention does not need to estimate the Doppler frequency modulation slope parameter required by the traditional method, thus the calculation speed is faster;

[0051] (5) This invention does not require the use of radar operating wavelength parameters, and the input parameters for the algorithm are fewer than those of traditional methods;

[0052] (6) The present invention has a small computational load and low processor computing resource consumption;

[0053] (7) The present invention has a clear concept, a simple algorithm, is easy to understand, and is easy to implement in engineering. Attached Figure Description

[0054] Figure 1 A schematic diagram of the geometric relationship for SAR motion parameter estimation;

[0055] Figure 2 This is a schematic diagram of the overall process of the present invention;

[0056] Figure 3 This is a schematic diagram illustrating the relationship between radar range estimation error and direction finding error and time of arrival measurement error in Example 3.

[0057] Figure 4 This is a schematic diagram illustrating the relationship between radar flight speed estimation error and direction finding error and time of arrival measurement error in Example 3.

[0058] Figure 5 This is a schematic diagram illustrating the relationship between the radar flight direction estimation error and the direction finding error and arrival time measurement error in Example 3. Detailed Implementation

[0059] The technical solution of the present invention will be described in detail below, but the scope of protection of the present invention is not limited to the embodiments described.

[0060] SAR (Radar Array Transmission) typically transmits linear frequency modulated (LFM) pulses to achieve high range resolution. SAR transmits pulse signals at fixed intervals. Traditional radar pulse arrival time measurement is generally achieved by reading the count value of a digital counter under the control of the pulse leading edge. The subtraction of the count values ​​obtained from adjacent pulse leading edges gives the radar repetition period. This method has two problems limiting measurement accuracy. One is the threshold comparison problem. Due to the influence of noise and signal amplitude, the moment the pulse leading edge exceeds the threshold will jitter, thus introducing measurement errors. The other problem is that because digital counting is used, continuous measurement of pulse arrival time cannot be provided; that is, the measurement value is always in units of counter counting periods. This invention utilizes the characteristic of SAR transmitting LFM pulses to achieve continuous measurement of pulse arrival time. After the LFM pulses transmitted by the SAR are detected by the radar countermeasure system, they undergo down-conversion, filtering, amplification, and quadrature demodulation to obtain a baseband LFM complex signal. The center frequency of this baseband LFM complex signal is fixed. This invention achieves continuous and accurate measurement of the arrival time of each pulse by measuring the position of its zero frequency and using this as the pulse arrival time.

[0061] like Figure 1As shown, the radar transmits a pulse at time t. At this time, the distance r between the radar and the receiving antenna is given by... Figure 1 have to

[0062]

[0063] The second equation above is obtained through a second-order Taylor expansion. Let θ = β - α0, equation (7) can be simplified to

[0064]

[0065] Then the time it takes for the pulse transmitted at time t to reach the receiving system is:

[0066]

[0067] Example 1;

[0068] like Figure 2 As shown, the SAR motion parameter estimation method based on accurate measurement of arrival time and direction of arrival in this embodiment includes the following steps:

[0069] Step (1): Read N LFM arrival directions and corresponding arrival times, and denot them as α. n and t n , n is the pulse number, n = 0, 1, 2, ..., N-1; direction of arrival refers to the line-of-sight angle of the jamming system to the radar.

[0070] Here, the SAR pulse repetition interval is set to T, and the arrival time of the 0th detected pulse is taken as time 0. Then, from equation (9), the arrival time of the nth pulse can be expressed as:

[0071]

[0072] Step (2): Use the least squares method to measure the line-of-sight angle α. n Perform a cubic polynomial fit to smooth out the error in the measured values.

[0073] Step (3): Use the least squares method to calculate the arrival time t. n By performing a quadratic polynomial fitting to smooth out the error of the measured values, the coefficients of the first term p1 and the coefficients of the second term p2 are obtained. That is, by measuring the arrival time of multiple pulses, the system of equations is established using equation (10) and solved as follows:

[0074]

[0075] At this point, the following equation can be obtained from equation (11):

[0076] 2p2r0+(p1-cT) 2 =(vT)2 (12)

[0077] Let Δr(n) represent the distance between the radar transmitting the nth pulse and the distance transmitting the 0th pulse. From equations (10) and (11), we can obtain:

[0078] Δr n =c(a n -nT)=(p1-cT)n+p2n 2 (13)

[0079] Let the line-of-sight angle when the radar transmits the nth pulse be α. n Let γ n =α n -α0, according to the cosine formula, from Figure 1 achievable

[0080]

[0081] Step (4): Use the statistical pulse arrival time difference to obtain the radar pulse repetition interval T;

[0082] First, calculate b n =a n+1 -a n ,0≤n <N-1 (21)

[0083] Then, count b n The histogram, the b corresponding to the peak in the histogram n The value is taken as T;

[0084] Among them, a n+1 This refers to the arrival time t n+1 The measured line-of-sight angle.

[0085] Step (5): Update the detected pulse sequence number n;

[0086]

[0087] Where, round(·) is the rounding function; if there is no pulse loss between adjacent pulses, then round(b n / T)=1; conversely, if there is a pulse loss between adjacent pulses, then round(b n / T)>1.

[0088] Step (6): Solve for the initial radar range r0 by combining equations (12), (13) and (14);

[0089]

[0090] In the above formula,

[0091]

[0092]

[0093] h n =-2cp2n 3 (19)

[0094]

[0095] According to u n v n w n h n and q n To solve for r0;

[0096] γ n =α n -α0, where α0 is the line-of-sight angle at arrival time t0, and c is the speed of light.

[0097] Step (7): Using the radar initial range r0 and arrival direction α obtained above... n and arrival time t n Solve for the radar's flight speed v and flight direction β;

[0098] First, using the radar's initial range r0 and direction of arrival α... n and arrival time t n Solve for the components of the flight velocity v in the X and Y directions. x v y ;

[0099] Then, using v x v y Then the radar flight speed v can be obtained as:

[0100] The direction of flight β is:

[0101] Example 2

[0102] This embodiment adopts the seven steps of Embodiment 1, using the arrival direction and arrival time information of N LFM pulses to estimate radar motion parameters. The overall computational complexity analysis includes the following:

[0103] 1) Use the least squares method to perform cubic curve fitting on the measured N line-of-sight angles to smooth the direction-finding error, which requires approximately 42N real number operations.

[0104] 2) The least squares method is used to fit the arrival time of the N pulses to a quadratic curve. While smoothing the direction finding error, the coefficients of the first term p1 and the second term p2 in equation (10) are obtained. Approximately 25N real number operations are required.

[0105] 3) After solving the quadratic equation to obtain r0, use the least squares method to solve equation (4) to obtain the flight speed v and flight direction β, which requires about 11N real number operations.

[0106] In summary, the required computation is less than 80N real number operations. Therefore, this method has very low requirements for processor computing resources.

[0107] Example 3

[0108] As can be seen from the motion parameter estimation equation given by equation (15), the accuracy of motion parameter estimation based on pulse arrival time and direction of arrival measurements depends solely on the measurement accuracy of pulse arrival time and direction of arrival. Due to the complexity of equation (15), it is very difficult to establish an analytical expression between the motion parameter estimation accuracy and the measurement accuracy of pulse arrival time and direction of arrival. Therefore, a better solution is to use simulation to examine and analyze the influence of pulse arrival time and direction of arrival measurement accuracy on the motion parameter estimation accuracy, and from this, the requirements for pulse arrival time and direction of arrival measurement accuracy can also be determined by inverse calculation based on the requirements for motion parameter estimation accuracy.

[0109] The simulation parameters for this embodiment are:

[0110] Radar flight speed v: 100 m / s; radar flight direction β: 90 degrees; radar initial range r0: 10 km; radar initial line-of-sight angle α0: -2.865 degrees, -45 degrees; radar pulse repetition interval: 1 ms; number of detected pulses: 1024, equivalent to the radar flying for 1.023 seconds, approximately 100 meters; radar line-of-sight angle measurement error range: 0–0.5 degrees; radar line-of-sight angle measurement error distribution: uniform distribution; radar pulse arrival time measurement error range: 0–0.5 ns; radar pulse arrival time measurement error distribution: uniform distribution; number of Monte Carlo simulations: 1000.

[0111] When the radar's initial line-of-sight angle α0 is -2.865 degrees, it is equivalent to the SAR operating in a frontal side-looking or small squint mode (the line of sight is perpendicular to the flight path); correspondingly, when α0 is -45 degrees, it is equivalent to the SAR operating in a large squint mode with a squint angle of 45 degrees.

[0112] The simulation results of this embodiment are as follows: Figures 3-5 As shown in Tables 1 to 6.

[0113] Figures 3-5The relationship between radar range, flight speed, and flight direction estimation errors and direction finding errors and arrival time measurement errors is shown in three-dimensional graphics for both frontal and oblique view modes.

[0114] Tables 1 and 2 present the specific simulation results showing the changes in radar range with direction-finding error and time-of-arrival measurement error in frontal and side-looking modes, respectively. In the tables, the first row represents the direction-finding error in degrees, and the first column represents the time-of-arrival measurement error in milliseconds (ns).

[0115] Table 1. Distance estimation error (m) in frontal and side-view modes.

[0116]

[0117]

[0118] Table 2. Distance estimation error (m) under oblique view mode.

[0119]

[0120]

[0121] Tables 3 and 4 present the specific simulation results showing the variations in radar flight speed and direction estimation errors with direction-finding error and time-of-arrival measurement error in frontal and side-looking modes, respectively. In the tables, the first row represents the direction-finding error in degrees, and the first column represents the time-of-arrival measurement error in milliseconds (ns).

[0122] Table 3. Flight speed estimation error (m / s) in frontal and side-view mode.

[0123]

[0124]

[0125] Table 4. Flight speed estimation error (m / s) in oblique view mode.

[0126]

[0127]

[0128] Tables 5 and 6 present the specific simulation results showing the variation of radar flight direction estimation error with direction finding error and time of arrival measurement error in frontal and side-looking modes, respectively. In the tables, the first row represents the direction finding error in degrees, and the first column represents the time of arrival measurement error in nanoseconds (ns).

[0129] Table 5. Flight direction estimation error (degrees) in frontal and side-view mode.

[0130]

[0131]

[0132] Table 6. Flight direction estimation error (degrees) under oblique view mode.

[0133]

[0134] The simulation results above show that:

[0135] 1) In the frontal side-view mode, the accuracy of motion parameter estimation is higher than that in the oblique-view mode. This is because in the frontal side-view mode, the range of change in the line-of-sight angle is greater than that in the oblique-view mode when the radar flies the same distance;

[0136] 2) Radar range estimation errors are more sensitive to time of arrival measurement errors, while radar flight speed and flight direction estimation errors are more sensitive to direction of arrival measurement errors. This is determined by the principle of this invention; furthermore, it can be seen that the radar flight direction estimation error is even basically unrelated to the time of arrival measurement error.

[0137] 3) As long as the measured radar pulse arrival direction and arrival time have sufficiently high accuracy, the present invention can provide a relatively accurate estimate of radar motion parameters.

[0138] For example, with a direction-finding error of 0.1 degrees and a time-of-arrival measurement error of 0.1 ns, using only 1024 pulses, even when the radar is operating in oblique-look mode, the estimation errors for radar range, flight speed, and flight direction are only 274.5 m, 8.51 m / s, and 4.91 degrees, respectively. This is difficult to achieve using traditional methods based on phase difference rate of change and Doppler frequency modulation estimation. For example, simulation results show that for a direction-finding error of 0.1 degrees, the traditional radar motion parameter estimation method based on the principle of particle kinematics has a range estimation error of 3000 m, a flight speed estimation error of 300 m / s, and a flight direction estimation error of 60 degrees. Such estimation accuracy is simply unusable in engineering. To achieve the same estimation accuracy as this invention, the direction-finding error must be less than 0.01 degrees. Therefore, this invention significantly reduces the requirements for direction-finding accuracy.

[0139] Example 4

[0140] This embodiment measures the arrival time. Using modern direction finding technology based on phase interferometer, the direction finding accuracy can easily reach below 0.1 degrees. Simulation results even show that it can reach 0.01 degrees. Therefore, the key to this invention is the measurement of arrival time.

[0141] Existing traditional radar pulse arrival time measurement methods cannot guarantee sub-nanosecond level measurement accuracy. However, by utilizing the characteristic of SAR transmitting LFM pulses and based on high-precision frequency measurement algorithms, accurate measurement of SAR transmitted pulse arrival time can be achieved.

[0142] For the SAR in this embodiment, the frequency modulation slope of its transmitted LFM pulse is generally several times greater than 10. 13 Hz / s, even for ordinary pulse compression radar, the frequency modulation slope is close to 10. 13 Hz / s. For example, an LFM pulse with a pulse width of 1μs and a bandwidth of 10MHz has a frequency modulation slope of 10 Hz / s. 13 Hz / s. Modern high-precision frequency measurement algorithms can achieve a frequency measurement accuracy on the order of 1kHz; therefore, the arrival time measurement accuracy can reach 1kHz / 10. 13 Hz / s = 0.1ns.

[0143] Table 7 presents the simulation results of the LFM pulse arrival time measurement accuracy in this embodiment.

[0144] The simulation parameters are as follows: pulse width: 4μs; LFM bandwidth: 120MHz; sampling frequency: 150MHz, 2.4GHz; signal-to-noise ratio range: 5~15dB; Monte Carlo simulations: 1000.

[0145] In this embodiment, the sampling rates of 150MHz and 2.4GHz in the simulation parameters represent the baseband sampling rate and the intermediate frequency sampling rate, respectively, and the frequency modulation slope of the LFM pulse is 3×10. 13 Hz / s. For pulses of the same width, different sampling rates result in different numbers of sampling points, which in turn affects measurement accuracy.

[0146] The simulation results of the pulse arrival time measurement error are shown in Table 7.

[0147] Table 7 Simulation results of pulse arrival time measurement error (ns)

[0148]

[0149] As shown in the table above, when the signal-to-noise ratio is 10dB, the pulse arrival time measurement error is less than 0.1ns, which is perfectly suitable for radar motion parameter estimation. Simulation results also strongly demonstrate that the radar motion parameter estimation method based on high-precision measurement of SAR transmitted pulse arrival direction and arrival time is feasible.

Claims

1. A method for estimating SAR motion parameters based on accurate measurements of arrival time and direction of arrival, characterized in that, Includes the following steps: Step (1) Read The measured values ​​of the arrival direction and corresponding arrival time of each LFM are denoted as follows: and n is the pulse number. The direction of arrival refers to the line-of-sight angle of the jamming system to the radar. Step (2): Use the least squares method to determine the line of sight angle. Perform cubic polynomial fitting to smooth out the error in the measured values; Step (3): Use the least squares method to calculate the arrival time. Perform a quadratic polynomial fitting to smooth out the measurement errors, and then obtain the coefficients of the first term. and quadratic coefficient ; Step (4): Use statistical pulse arrival time difference to obtain radar pulse repetition interval. ; First calculate ; Then, the difference in arrival time between adjacent pulses is calculated. The histogram, the peak value in the histogram corresponds to... Value as ; Step (5): Update the detected pulse sequence number ; ; in, This is a rounding function; if no pulses are lost between adjacent pulses, then... ; Conversely, if there is a pulse loss between adjacent pulses, then ; Step (6): Solve for the initial radar range The specific method is as follows: ； In the above formula, ; ； ； ； ； according to , , , and Seeking a solution ; , for The line-of-sight angle at which the pulse arrives at the moment. The speed of light; , , , and All are intermediate calculations Step (7): Using the radar initial range obtained above , destination and arrival time Solve for radar flight speed and flight direction .

2. The SAR motion parameter estimation method based on accurate measurement of arrival time and direction of arrival as described in claim 1, characterized in that, The radar flight speed is obtained by solving step (7). and flight direction The specific method is as follows: First, through radar initial distance , destination and arrival time Solve for the components of the flight velocity in the X and Y directions. , ; Then, using , Then the radar flight speed can be obtained. for: ; Flight direction Then it is: .

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