Radar jitter compensation method and system based on coherent processing cycle update

Abstract

The invention provides a radar jitter compensation method and system based on coherent processing cycle update. The method comprises the following steps: S1, collecting a coarse path of a motion platform of a radar; the coarse path is selected from inertial navigation data of a radar; s2, carrying out distance compression on the echo data to obtain a coarse image of the echo data; s3, collecting a special display point according to the coarse image; s4, performing nonlinear optimization on the echo process, the phase process and the coarse path, and outputting a platform position after jitter error compensation; and feeding back the positioning information of the platform position to the inertial navigation data. According to the method, a coherent processing cycle updating mode is adopted, the platform jitter error at each pulse moment is corrected, and the problem that imaging, recognition and the like are affected due to the poor later radar data processing effect caused by platform position information errors in a strong clutter environment, especially in a penetrating scene is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar signal processing, and in particular, relates to a radar jitter compensation method and system based on coherent processing periodic updating. Background Art

[0002] Radar scanning platforms, such as right-angle automatic scanning brackets, drone-mounted platforms and other automatic platforms, usually run along a fixed preset trajectory. However, in actual applications, the motion platform equipped with wall-penetrating radar has position errors caused by jitter due to the vibration characteristics generated by the working of the motor, human control and other reasons.

[0003] The wall-penetrating radar payload is based on ultra-wideband signals with a stepped frequency system and has a high range resolution. Therefore, the impact of the platform's jitter error on the echo cannot be ignored.

[0004] Generally speaking, a motion platform can obtain its own position information by carrying an inertial measurement unit, or IMU, and a satellite navigation system. Both of these play a very limited role in motion platforms in urban or laboratory environments.

[0005] IMU includes gyroscopes and accelerometers, which can obtain the three-dimensional angular velocity information and acceleration information of the platform in real time, and obtain the platform's position information through attitude conversion and track deduction. However, due to hardware limitations and noise influences, IMU itself cannot accurately obtain the jitter error information, and the motion trajectory based on inertial navigation also has cumulative drift, which is not suitable for recording the actual platform position information within the period of time required by the synthetic aperture; in particular, in the complex application environment of wall-penetrating radar, during high-altitude flight close to buildings, the communication of Beidou satellites is sometimes interrupted, and satellite positioning may also be unstable. These realistic conditions limit the means of eliminating platform jitter errors from a hardware perspective.

[0006] Patent document CN111505621A discloses a method and device for fine-grained moving target positioning for a moving platform. This solution relates to the field of moving target positioning technology and is suitable for high-precision positioning of moving platforms, especially high-speed moving platforms. It uses inertial navigation information to compensate for the non-ideal motion of the moving platform, corrects the good channel data and the bad channel data, and achieves fine positioning of ground moving targets through fine instantaneous interference phase estimation, which can meet the positioning requirements of high-speed moving platforms. However, this solution cannot eliminate platform jitter errors.

[0007] This problem needs to be solved urgently. Summary of the invention

[0008] In view of the defects in the prior art, an object of the present invention is to provide a radar jitter compensation method and system based on coherent processing periodic update.

[0009] A radar jitter compensation method based on coherent processing periodic update provided by the present invention includes:

[0010] Step S1: collecting a rough path of the motion platform of the radar; the rough path is obtained from the inertial navigation data of the radar;

[0011] Step S2: distance compressing the echo data to obtain a coarse image of the echo data;

[0012] Step S3: collecting distinctive points according to the coarse image; extracting echo history and phase history according to the distinctive points;

[0013] Step S4: nonlinearly optimize the echo history, phase history and the coarse path, output the platform position after jitter error compensation; and feed back the positioning information of the platform position to the inertial navigation data.

[0014] Preferably, in step S1, the coarse path is the position of the radar at each pulse time obtained based on the track inference of the inertial sensor;

[0015] When the motion platform of the radar moves in a uniform linear motion along the azimuth direction, the platform position at the mth moment is expressed mathematically as follows:

[0016] p a,m =p a,m-1 +u m +1

[0017] Among them, p a,m is the platform position at the mth moment; p a,m-1 is the platform position at the m-1th moment; u m is the position increment at the mth moment obtained by IMU, w m is the platform jitter error.

[0018] Preferably, in the step S2, when the motion platform moves in a uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows:

[0019]

[0020] Among them, v m is the platform motion parameter estimation result based on the Doppler parameters in the echo, that is, the radar motion speed; δ m is the instantaneous velocity at time m; the symbol ||||1 is the L1 norm;

[0021] The δ mThe mathematical expression is:

[0022]

[0023] Among them, p a,0 is the platform position at the start time, Δt m is the slow time interval;

[0024] In the step S2, when the motion platform performs non-uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows:

[0025]

[0026] Among them, v m is the radar speed at time m, γ m is the Doppler frequency; R B is the vertical distance; λ is the wavelength.

[0027] Preferably, in step S3, the slant range error caused by the platform shaking is compensated; the observation equation of the slant range error is expressed as follows:

[0028]

[0029] Among them, p a,m is the platform position at time m; v m is the radar speed at time m; γ m,k Indicates the distance between the actual position of the platform at the mth pulse moment and the kth prominent point; Δγ m,k represents the observation equation, i.e., the slope range error; f1 is related to the parameter p a,m-1 ,u m ,w m related function; f2 is related to p a,0 ,p a,m related functions; f3 is related to p a,m ,p p,k Related functions; f4 is related to p a,m ,u m ,w m ,p p,k Related functions; u m Indicates position increment; p p,f represents the position of the platform at time f.

[0030] Preferably, in step S4, noise reduction processing is performed, and the position increment, the radar motion speed, the target slant range and the slant range error are nonlinearly optimized;

[0031] The mathematical expression of the noise reduction process is:

[0032]

[0033] Among them, e 1,m Represents an introduced error; e 2,m Represents another kind of error introduced; e 3,m Represents another error introduced; e 4,m Indicates another introduced error;

[0034] Based on the position increment, the radar movement speed, the target slant range and the slant range error, a least squares equation is constructed, and the mathematical expression is:

[0035]

[0036] Where, J(x) represents the slant range error; the superscript T represents the time; Indicates that 1,m The inverse of the corresponding covariance matrix; Indicates that 2,m The inverse of the corresponding covariance matrix; It represents the third kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix; e 3,m,k represents the slant range measurement error of the special point k at the mth pulse moment; e 4,m,k It represents the fourth kind of slant range measurement error of the special point k at the mth pulse time; It represents the fourth kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix;

[0037] According to the least squares equation, the imaging result is obtained, and the mathematical expression is:

[0038]

[0039] in, It represents the solution to the optimization problem, that is, the estimated value of the parameter x obtained by minimizing the objective function J(x); argmin represents a mathematical operator that finds the minimum value of the subsequent function; the symbol ||||2 represents the sign of the L2 norm.

[0040] According to the present invention, a radar jitter compensation system based on coherent processing periodic update is provided, comprising:

[0041] Module M1: collects the rough path of platform movement; the rough path is taken from the inertial navigation data of the radar;

[0042] Module M2: distance compressing echo data to obtain a coarse image of the echo data;

[0043] Module M3: collecting distinctive points according to the coarse image; extracting echo history and phase history according to the distinctive points;

[0044] Module M4: nonlinearly optimizes the echo history, phase history and the coarse path, outputs the platform position after jitter error compensation; and feeds back the positioning information of the platform position to the inertial navigation data.

[0045] Preferably, in the module M1, the coarse path is the position of the radar at each pulse time obtained based on the track inference of the inertial sensor;

[0046] When the motion platform of the radar moves in a uniform linear motion along the azimuth direction, the platform position at the mth moment is expressed mathematically as follows:

[0047] p a,m =p a,m-1 +u m +1

[0048] Among them, p a,m is the platform position at the mth moment; p a,m-1 is the platform position at the m-1th moment; u m is the position increment at the mth moment obtained by IMU, w m is the platform jitter error.

[0049] Preferably, in the module M2, when the motion platform moves in a uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows:

[0050]

[0051] Among them, v m is the platform motion parameter estimation result based on the Doppler parameters in the echo, that is, the radar motion speed; δ m is the instantaneous velocity at time m; the symbol ||||1 is the L1 norm;

[0052] The δ m The mathematical expression is:

[0053]

[0054] Among them, p a,0 is the platform position at the start time, Δt m is the slow time interval;

[0055] In the module M2, when the motion platform performs non-uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows:

[0056]

[0057] Among them, v m is the radar movement speed, γ m is the Doppler frequency; R B is the vertical distance; λ is the wavelength.

[0058] Preferably, in the module M3, the slant range error caused by the platform jitter is compensated; the observation equation of the slant range error is expressed as follows:

[0059]

[0060] Among them, f1 is related to the parameter p a,m-1 ,u m ,w m related function; f2 is related to p a,0 ,p a,m related functions; f3 is related to p a,m ,p p,k Related functions; f4 is related to p a,m ,u m ,w m ,p p,k Related function; Δγ m,k represents the observation equation, i.e., the slant range error; u m Indicates position increment; p p,f represents the position of the platform at time f; p p,k represents the position of the platform at time k;

[0061] Preferably, in the module M4, noise reduction processing is performed, and the position increment, the radar movement speed, the target slant range and the slant range error are nonlinearly optimized;

[0062] The mathematical expression of the noise reduction process is:

[0063]

[0064] Among them, e 1,m Represents an introduced error; e 2,m Represents another kind of error introduced; e 3,m Represents another error introduced; e 4,m Indicates another introduced error;

[0065] Based on the position increment, the radar movement speed, the target slant range and the slant range error, a least squares equation is constructed, and the mathematical expression is:

[0066]

[0067] Where, J(x) represents the slant range error; the superscript T represents the time; Indicates that 1,m The inverse of the corresponding covariance matrix; Indicates that 2,m The inverse of the corresponding covariance matrix; It represents the third kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix; e 3,m,k represents the slant range measurement error of the special point k at the mth pulse moment; e 4,m,k It represents the fourth kind of slant range measurement error of the special point k at the mth pulse time; It represents the fourth kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix;

[0068] According to the least squares equation, the imaging result is obtained, and the mathematical expression is:

[0069]

[0070] in, It represents the solution to the optimization problem, that is, the estimated value of the parameter x obtained by minimizing the objective function J(x); argmin represents a mathematical operator that finds the minimum value of the subsequent function; the symbol ||||2 represents the sign of the L2 norm.

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] 1. The present invention eliminates the platform jitter error from the software perspective, making up for the problems that the IMU and other units themselves are subject to hardware limitations, noise influences, etc., and the accumulated drift of the motion trajectory based on other inertial navigation calculations, which makes it impossible to accurately obtain the real-time position of the platform and eliminate the defects of platform jitter.

[0073] 2. The present invention adopts the method of "coarse imaging" followed by "fine process extraction" to obtain the prominent points from the coarse imaging results, and then reversely extracts the echo process and phase process of the prominent points, and inputs them into the nonlinear optimization method together with the coarse path. The optimization method outputs the platform position after jitter error compensation, and feeds back the corrected positioning information to the platform positioning sensor to ensure the accuracy of the platform motion trajectory.

[0074] 3. The present invention adopts a coherent processing periodic update method to correct the platform jitter error at each pulse moment, thereby solving the problems of poor post-processing of radar data affecting imaging and recognition due to erroneous platform position information in a strong clutter environment, especially in a penetration scenario.

[0075] 4. The present invention reversely compensates for the jitter effect of an unstable platform based on radar echo information of a prominent point in the environment, thereby minimizing the impact of the platform position error on subsequent target detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0077] Figure 1 This is a schematic diagram of the motion platform position correction process provided by the present invention. DETAILED DESCRIPTION

[0078] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0079] In view of the above-mentioned defects in the prior art, the technical problems to be solved by the present invention are embodied in the following points:

[0080] 1. The present invention reduces the interference of jitter errors caused by the radar platform on the radar echo signal, and improves the robustness, adaptability and accuracy of the radar motion platform;

[0081] 2. The present invention eliminates the influence of the accumulated drift of the motion trajectory based on inertial navigation on the real-time positioning of the platform;

[0082] 3. The present invention solves the problem that in a strong clutter environment, especially in a penetration scenario, the one-dimensional range image has many echo tails, which makes it difficult to extract feature points during radar imaging.

[0083] The present invention provides a radar jitter compensation method based on coherent processing periodic update. It includes a coarse path extraction module, a coarse imaging module, a prominent point and its course extraction module, a nonlinear optimization module and a platform jitter error compensation module. In the process of the motion platform hovering and synchronously recording radar echoes, the echo information arrives over time, and the same prominent point is often observed by the radar multiple times at different positions, and the radar observes more than one prominent point at the same time.

[0084] In addition, in the actual urban building environment, there are a large number of strong scattering objects such as wall corners, window frames, door frames, etc., which can be regarded as dihedral or trihedral angles. Therefore, each echo pulse contains a large number of static prominent points. These factors are intertwined, giving the optimization process more constraints. It is possible to better recover the positioning information from the echo data. Therefore, this method intends to use the coherent processing cycle, namely the Coherent Processing Interval, referred to as the CPI update method, to correct the platform jitter error at each pulse moment. The motion platform position correction process based on radar prominent points, such as Figure 1 As shown in the figure, each module is connected in sequence according to the data flow order.

[0085] The first step is to obtain the rough path of the platform movement from the inertial navigation data of the radar platform or other positioning sensors. The rough path module is extracted from the inertial navigation data.

[0086] The second step is to obtain a coarse image of the radar echo data by performing distance compression on the original echo data; the coarse image, i.e., a rough image, usually refers to an initial image obtained after preliminary processing or simple algorithm calculation. This image may not have high resolution and unclear details, and is mainly used to quickly evaluate the approximate position and shape of the target object; in other words, the coarse image is used to evaluate the position and shape of the target object.

[0087] In the third step, after obtaining the prominent points from the coarse imaging, the prominent point and its process extraction module reversely extracts the echo process and phase process of the prominent points, and inputs them into the nonlinear optimization module together with the coarse path;

[0088] In the fourth step, the nonlinear optimization module optimizes the echo and phase history, outputs the platform position after jitter error compensation, and feeds back the corrected positioning information to the inertial navigation data or platform to ensure the accuracy of the platform motion trajectory.

[0089] Implementation Example 1: Taking the detection and imaging of stationary targets inside the wall by a wall-penetrating radar based on a fully automatic scanning platform as an example, this paper provides a radar jitter compensation method based on coherent processing cycle update. It includes a coarse path extraction module, a coarse imaging module, a prominent point and its course extraction module, a nonlinear optimization module and a platform jitter error compensation module. In the process of the motion platform hovering and synchronously recording radar echoes, the echo information arrives over time, and the same prominent point is often observed by the radar multiple times at different positions, and the radar observes more than one prominent point at the same time. In addition, in the actual urban building environment, there are a large number of strong scattering objects such as wall corners, window frames, door frames, etc., which can be regarded as dihedral or trihedral angles, so each echo pulse contains a large number of static prominent points. These factors are intertwined, giving the optimization process more constraints. It is possible to better recover the positioning information from the echo data. Therefore, this method intends to adopt a coherent processing cycle, namely, Coherent Processing Interval, referred to as CPI update, to correct the platform jitter error at each pulse moment. The specific implementation method of the invention is as follows:

[0090] In the first step, a rough path of platform motion is obtained from the radar platform's inertial navigation data or other positioning sensors.

[0091] Assume the initial position of the radar airborne path, i.e., p a,0 It is known that the coarse path is the position of the radar at each pulse time obtained by inferring the track based on the IMU, that is, p a,m , according to the envelope and phase information provided by the historical echo, and the track information provided by the IMU, the motion equation and observation equation are established respectively. Assume that the motion platform moves in a uniform straight line along the azimuth direction. Then the platform position at the mth moment is:

[0092] p a,m =p a,m-1 +u m +1

[0093] Among them, p a,m is the platform position at the mth moment; p a,m-1 is the platform position at the m-1th moment; u m is the position increment at the mth moment obtained by IMU, w m is the platform jitter error.

[0094] The second step is to obtain a rough image of the radar echo data by performing range compression on the original echo data.

[0095] Under the premise of uniform linear motion, the historical position of the platform trajectory should satisfy

[0096]

[0097] Among them, v m is the platform motion parameter estimation result based on the Doppler parameters in the echo; δ m is the instantaneous velocity at time m; the symbol ||||1 is the L1 norm;

[0098] The δ m The mathematical expression is:

[0099] δ m =(δ1,δ2,...δ m )

[0100]

[0101] Among them, p a,0 is the platform position at the start time, Δt m Slow time interval.

[0102]

[0103] Among them, γ m is the Doppler frequency; R B is the vertical distance; λ is the wavelength;

[0104] Assuming that there is no acceleration parallel or perpendicular to the route direction during the UAV movement, the instantaneous Doppler frequency γ is extracted through the historical echo phase m , R B is the vertical distance, and the motion parameters of the radar can be estimated.

[0105] The observation equation is analyzed below. The observation equation mainly uses the platform position and the prominent point p outside the wall. p,k The distance between them is established. After compressing the historical signal pulse, the distance information of the peak value can be extracted. The observation equation of the actual distance is obtained:

[0106] γ m,k =||p a,m -p p,k ||2

[0107] Among them, γ m,k is the distance between the actual position of the platform at the mth pulse moment and the kth prominent point; p p,k It is a prominent point outside the wall;

[0108] In the third step, after obtaining the prominent points from the coarse imaging, the prominent point and its history extraction module reversely extracts the echo history and phase history of the prominent points, and inputs them into the nonlinear optimization module together with the coarse path; the echo history represents all historical echoes up to the current moment, and the echo history is preprocessed, including pulse compression, coarse imaging, range gate extraction of the feature points, phase extraction and motion parameter estimation.

[0109] Next, let’s consider the slant range error caused by platform jitter. For targets outside the wall, assuming that the moving platform moves in a uniform straight line, the ideal echo history should conform to a quadratic function. After the platform runs for a period of time and accumulates enough history, the echo history at the peak of the prominent point in front of the wall is fitted with a quadratic curve to estimate the slant range error Δγ. m,k :

[0110]

[0111] Among them, Δγ m,k represents the slope range error; r m,k represents the distance between the actual position of the platform at the time of the mth pulse and the kth prominent point; β represents the jitter coefficient related to the platform acceleration; t m represents the time of the mth pulse; φ0 represents the distance offset at the initial time;

[0112] The difference between the ideal track of the platform and the actual track of the platform is caused by the platform shaking, so the slant range error can also be expressed as:

[0113]

[0114] in, It represents the slant distance between the platform and the target, i.e., the kth prominent point at the mth pulse time under the actual trajectory; It represents the slant distance between the platform and the target, i.e. the kth prominent point at the mth pulse time, under the ideal trajectory.

[0115] Based on the above relationship, the observation equation of the target in front of the wall regarding the slant range error can be obtained as follows:

[0116] Δγ m,k =||p a,m-1 +u m -p p,f ||2-||p a,m-1 +u m +w m -p p,f ||2

[0117] Among them, Δγ m,k represents the observation equation; u m Indicates position increment; p p,f represents the position of the platform at time f; w m Indicates the platform jitter error;

[0118] The above observation equations can be written uniformly as:

[0119]

[0120] Among them, f1 is related to the parameter pa,m-1 ,u m ,w m related function; f2 is related to p a,0 ,p a,m related functions; f3 is related to p a,m ,p p,k Related functions; f4 is related to p a,m ,u m ,w m ,p p,k Related function; Δγ m,k represents the observation equation, i.e., the slant range error; u m Indicates position increment; p p,f represents the position of the platform at time f.

[0121] In the fourth step, the nonlinear optimization module optimizes the echo and phase history, outputs the platform position after jitter error compensation, and feeds back the corrected positioning information to the inertial navigation data or platform to ensure the accuracy of the platform motion trajectory. m and the radar velocity v provided by the echo history m , target slope range γ m,k , Slope range error Δγ m,k The known measurement information is used for nonlinear optimization, and the compensated accurate radar position is finally output.

[0122] The above formula represents an ideal situation. In actual processes, the acquired data is affected by various noises, and the model proposed above can only be as accurate as possible. Therefore, noise is introduced below to consider how to perform accurate state estimation in noisy data.

[0123]

[0124] Among them, e 1,m , e 2,m , e 3,m , e 4,m represents the error introduced to represent the noise;

[0125] In other words, e 1,m Represents an introduced error; e 2,m Represents another kind of error introduced; e 3,m Represents another error introduced; e 4,m Indicates another introduced error;

[0126] Assume that the above errors all conform to the zero-mean Gaussian distribution:

[0127] e 1,m ~N(0,Q1),e 2,m ~N(0,Q2)

[0128] e 3,m ~N(0,Q3),e 4,m ~N(0,Q4)

[0129] Wherein, N represents the symbol of Gaussian distribution, Q1, Q2, Q3 and Q4 represent the variance of one introduced error, another introduced error, another introduced error and another introduced error respectively. Based on the position increment, the radar movement speed, the target slant range and the slant range error, a least squares equation is constructed, and the mathematical expression is:

[0130]

[0131] Where, J(x) represents the slant range error; the superscript T represents the time; Indicates that 1,m The inverse of the corresponding covariance matrix; Indicates that 2,m The inverse of the corresponding covariance matrix; It represents the third kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix; e 3,m,k represents the slant range measurement error of the special point k at the mth pulse moment; e 4,m,k It represents the fourth kind of slant range measurement error of the special point k at the mth pulse time; It represents the fourth kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix;

[0132]

[0133] in, It represents the solution to the optimization problem, that is, the estimated value of the parameter x obtained by minimizing the objective function J(x); argmin represents a mathematical operator that finds the minimum value of the subsequent function; the symbol ||||2 represents the sign of the L2 norm.

[0134] Finally, the least squares problem is solved by nonlinear optimization methods such as Gauss-Newton and Levenberg-Marquadt to obtain the platform position after jitter error compensation. Re-imaging with the compensated platform position information can obtain imaging results with better focusing effect.

[0135] The present invention also provides a radar jitter compensation system based on coherent processing cycle update. The radar jitter compensation system based on coherent processing cycle update can be implemented by executing the process steps of the radar jitter compensation method based on coherent processing cycle update, that is, those skilled in the art can understand the radar jitter compensation method based on coherent processing cycle update as a preferred implementation of the radar jitter compensation system based on coherent processing cycle update.

[0136] According to the present invention, a radar jitter compensation system based on coherent processing periodic update is provided, comprising:

[0137] Module M1: collects the rough path of platform movement; the rough path is taken from the inertial navigation data of the radar;

[0138] Module M2: distance compressing echo data to obtain a coarse image of the echo data;

[0139] Module M3: collecting distinctive points according to the coarse image; extracting echo history and phase history according to the distinctive points;

[0140] Module M4: nonlinearly optimizes the echo history, phase history and the coarse path, outputs the platform position after jitter error compensation; and feeds back the positioning information of the platform position to the inertial navigation data.

[0141] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0142] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A radar jitter compensation method based on coherent processing periodic update, characterized in that: include: Step S1: Collecting the rough path of the moving platform of the radar; The coarse path is taken from the inertial navigation data of the radar; Step S2: distance compressing the echo data to obtain a coarse image of the echo data; Step S3: collecting distinctive points according to the coarse image; extracting echo history and phase history according to the distinctive points; Step S4: nonlinearly optimize the echo history, phase history and the coarse path, output the platform position after jitter error compensation; and feed back the positioning information of the platform position to the inertial navigation data.

2. The radar jitter compensation method based on coherent processing periodic update according to claim 1, characterized in that: In step S1, the coarse path is the position of the radar at each pulse time obtained based on the inference of the inertial sensor track; When the motion platform of the radar moves in a uniform linear motion along the azimuth direction, the platform position at the mth moment is expressed mathematically as follows: pp a,m =p a,m-1 +u m +1 in, a,m is the platform position at the mth moment; p a,m-1 is the platform position at the m-1th moment; u m is the position increment at the mth moment obtained by IMU, w m is the platform jitter error.

3. The radar jitter compensation method based on coherent processing periodic update according to claim 2, characterized in that: In the step S2, when the motion platform moves in a uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows: Among them, v m is the platform motion parameter estimation result based on the Doppler parameters in the echo, that is, the radar motion speed; δ m is the instantaneous velocity at time m; the symbol ||||1 is the L1 norm; The δ m The mathematical expression is: Among them, p a,0 is the platform position at the start time, Δt m is the slow time interval; In the step S2, when the motion platform performs non-uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows: Among them, v m is the radar movement speed, γ m is the Doppler frequency; R B is the vertical distance; λ is the wavelength.

4. The radar jitter compensation method based on coherent processing periodic update according to claim 3, characterized in that: In step S3, the slant range error caused by the platform shaking is compensated; the observation equation of the slant range error is expressed as follows: Among them, f1 is related to the parameter p a,m-1 ,u m ,w m related function; f2 is related to p a,0 ,p a,m related functions; f3 is related to p a,m ,p p,k Related functions; f4 is related to p a,m ,u m ,w m ,p p,k Related function; Δγ m,k represents the observation equation, i.e., the slant range error; u m Indicates position increment; p p,f represents the position of the platform at time f.

5. The radar jitter compensation method based on coherent processing periodic update according to claim 4, characterized in that: In the step S4, noise reduction processing is performed, and the position increment, the radar movement speed, the target slant range and the slant range error are nonlinearly optimized; The mathematical expression of the noise reduction process is: Among them, e 1,m Represents an introduced error; e 2,m Represents another kind of error introduced; e 3,m Represents another error introduced; e 4,m Indicates another introduced error; Based on the position increment, the radar movement speed, the target slant range and the slant range error, a least squares equation is constructed, and the mathematical expression is: Where, J(x) represents the slant range error; the superscript T represents the time; Indicates that 1,m The inverse of the corresponding covariance matrix; Indicates that 2,m The inverse of the corresponding covariance matrix; It represents the third kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix; e 3,m,k represents the slant range measurement error of the special point k at the mth pulse moment; e 4,m,k It represents the fourth kind of slant range measurement error of the special point k at the mth pulse time; It represents the fourth kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix; According to the least squares equation, the imaging result is obtained, and the mathematical expression is: in, It represents the solution to the optimization problem, that is, the estimated value of the parameter x obtained by minimizing the objective function J(x); argmin represents a mathematical operator that finds the minimum value of the subsequent function; the symbol || ||2 represents the sign of the L2 norm.

6. A radar jitter compensation system based on coherent processing periodic update, characterized in that: include: Module M1: collects the rough path of platform movement; The coarse path is taken from the inertial navigation data of the radar; Module M2: distance compressing echo data to obtain a coarse image of the echo data; Module M3: collecting distinctive points according to the coarse image; extracting echo history and phase history according to the distinctive points; Module M4: nonlinearly optimizes the echo history, phase history and the coarse path, outputs the platform position after jitter error compensation; and feeds back the positioning information of the platform position to the inertial navigation data.

7. The radar jitter compensation system based on coherent processing periodic update according to claim 6, characterized in that: In the module M1, the coarse path is the position of the radar at each pulse time obtained based on the inference of the inertial sensor track; When the motion platform of the radar moves in a uniform linear motion along the azimuth direction, the platform position at the mth moment is expressed mathematically as follows: pp a,m =p a,m-1 +u m +1 Among them, p a,m is the platform position at the mth moment; p a,m-1 is the platform position at the m-1th moment; u m is the position increment at the mth moment obtained by IMU, w m is the platform jitter error.

8. The radar jitter compensation system based on coherent processing periodic update according to claim 7, characterized in that: In the module M2, when the motion platform moves in a uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows: Among them, v m is the platform motion parameter estimation result based on the Doppler parameters in the echo, that is, the radar motion speed; δ m is the instantaneous velocity at time m; the symbol ||||1 is the L1 norm; The δ m The mathematical expression is: Among them, p a,0 is the platform position at the start time, Δt m is the slow time interval; In the module M2, when the motion platform performs non-uniform linear motion, the historical position of the platform trajectory in the coarse image is expressed mathematically as follows: Among them, v m is the radar movement speed, γ m is the Doppler frequency; R B is the vertical distance; λ is the wavelength.

9. The radar jitter compensation system based on coherent processing periodic update according to claim 8, characterized in that: In the module M3, the slant range error caused by the platform jitter is compensated; the observation equation of the slant range error is expressed as follows: Among them, f1 is related to the parameter p a,m-1 ,u m ,w m related function; f2 is related to p a,0 ,p a,m related functions; f3 is related to p a,m ,p p,k Related functions; f4 is related to p a,m ,u m ,w m ,p p,k Related function; Δγ m,k represents the observation equation, i.e., the slant range error; u m Indicates position increment; p p,f represents the position of the platform at time f.

10. The radar jitter compensation system based on coherent processing periodic update according to claim 9, characterized in that: In the module M4, noise reduction processing is performed, and the position increment, the radar movement speed, the target slant range and the slant range error are nonlinearly optimized; The mathematical expression of the noise reduction process is: Among them, e 1,m Represents an introduced error; e 2,m Represents another kind of error introduced; e 3,m Represents another error introduced; e 4,m Indicates another introduced error; Based on the position increment, the radar movement speed, the target slant range and the slant range error, a least squares equation is constructed, and the mathematical expression is: Where, J(x) represents the slant range error; the superscript T represents the time; Indicates that 1,m The inverse of the corresponding covariance matrix; Indicates that 2,m The inverse of the corresponding covariance matrix; It represents the third kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix; e 3,m,k represents the slant range measurement error of the special point k at the mth pulse moment; e 4,m,k It represents the fourth kind of slant range measurement error of the special point k at the mth pulse time; It represents the fourth kind of slant range measurement error of the mth pulse moment corresponding to the special point k at time T; Representation and The inverse of the corresponding covariance matrix; According to the least squares equation, the imaging result is obtained, and the mathematical expression is: in, It represents the solution to the optimization problem, that is, the estimated value of the parameter x obtained by minimizing the objective function J(x); argmin represents a mathematical operator that finds the minimum value of the subsequent function; the symbol || ||2 represents the sign of the L2 norm.

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