CN110161478B - Waveform design method based on clutter power spectral density self-optimization - Google Patents
Waveform design method based on clutter power spectral density self-optimization Download PDFInfo
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Abstract
The invention provides a waveform design method based on clutter power spectral density self-optimization, which solves the technical problems of low accuracy and instantaneity of environmental clutter estimation in the prior art. The implementation steps are as follows: irradiating a scene, receiving radar echo data, and performing pulse compression processing to obtain a one-dimensional range profile; solving an autocorrelation function of the one-dimensional range profile, and performing Fourier transform on the autocorrelation function to obtain a clutter power spectrum function; comparing the obtained clutter power spectrum function with the clutter power spectrum function of the previous pulse to determine an environment updating mark and a final clutter power density; and judging an environment updating mark, and solving the phase of the optimal waveform by adopting a phase iteration method. The method estimates the clutter power spectrum density of the environment in real time, makes full use of the environment information, reduces unnecessary calculation by a clutter function error comparison method, effectively improves the signal-to-noise-and-noise ratio of the received signal, and improves the radar target detection performance.
Description
Technical Field
The invention belongs to the technical field of radar signal processing, relates to waveform optimization design based on environment perception, and particularly relates to a waveform design method based on clutter power spectral density self-optimization, which can be used for design of an optimal waveform in a complex environment and subsequent target detection and identification.
Background
Conventional radar systems typically transmit a fixed electromagnetic waveform to receive and process echo signals containing target, noise, interference, and ambient information, operating in an open-loop manner based on the echo data. In fact, the working environment of the radar system is complex and changeable, and when the clutter environment of the target changes, a single emission waveform, a solidified algorithm and parameter setting in the radar system cannot adapt to the change of the real environment, which will cause the signal-to-noise ratio of the radar system to be greatly reduced, and further cause the subsequent target detection and identification performance to be reduced.
An effective solution is to utilize environmental knowledge to improve the signal-to-noise ratio of radar echo under a complex background in a complex varying clutter environment. The echo data are processed by fully utilizing the prior information of the radar echo and the target, clutter distribution information in the complex environment of the current radar work is extracted and estimated, a radar emission waveform adaptive to the current clutter environment and the target characteristic is designed, and the signal-to-noise ratio of the radar echo and the target detection and identification capability of a radar system are improved. Therefore, how to estimate the distribution characteristics of the current clutter in a complex changing environment has important research value.
At present, people have made a lot of research on waveform optimization based on environmental perception, mainly by establishing a database for environmental data, using current environmental information, under the condition of constant envelope constraint and taking the maximum signal-to-noise-plus-noise ratio as the optimization criterion, directly solving the time domain signal of the optimal waveform or firstly calculating the frequency domain energy distribution representation of the optimal waveform, and then solving the time domain signal. In 2005, the DARPA and navy research laboratories jointly develop a self-adaptive waveform design research project for detecting the low-ground-angle small RCS target in the complex marine environment, and the detection, resolution and tracking performance of the low-ground-angle small RCS target under the condition of strong sea clutter is improved by real-time optimization of radar emission waveforms. In 2018, luzhu of electronics science and technology university provides a waveform design algorithm based on environment spectrum knowledge in his doctor paper, and the method mainly improves the detection performance of the radar in a spectrum crowded environment from the aspect of optimizing the waveform design of a radar transmitting end through the environment spectrum knowledge in a radar environment knowledge base constructed previously.
However, these waveform design methods are only suitable for the case where prior information is known or a radar environment database is established, and do not interact with the environment in real time to obtain required information, and when the radar working scene environment changes complicatedly and is not in the known database, the currently proposed waveform design methods cannot ensure the improvement of the signal-to-noise-ratio and the improvement of the detection performance.
Most of the existing waveform design methods based on environment sensing cannot acquire clutter distribution characteristics when the radar working environment changes and is not in a known database, and have the limitation that the accuracy cannot be improved in practical application.
Disclosure of Invention
The invention aims to overcome the limitations of the prior art and provides a waveform design method based on clutter power spectral density self-optimization with high accuracy and robustness.
The invention relates to a waveform design method based on clutter power spectral density self-optimization, which is characterized by comprising the following steps of:
(1) Acquiring a one-dimensional range profile corresponding to each pulse containing clutter distribution information: using radar linear frequency modulation signals to irradiate a scene which does not contain a target, considering that the scene contains clutter information of a target background environment, receiving radar echo data in the scene, and performing pulse compression processing on the real-time radar echo data to obtain one-dimensional range profiles of a plurality of radar linear frequency modulation signals, namely acquiring the one-dimensional range profiles corresponding to each pulse containing clutter distribution information; define the one-dimensional range profile of the current pulse as x = [ x ] 1 ,x 2 ,...,x m ] T ∈R N Wherein x is i The amplitude of the ith distance resolution unit is shown, R is a real number, N is a total dimension of a vector space, N is a positive integer, m is a serial number of the vector space dimension, m =1, 2.
(2) Solving an autocorrelation function R for a one-dimensional range profile x of a current pulse of a radar chirp signal xx ；
(3) Obtaining a clutter power spectrum function P (f) of the background environment: autocorrelation function R for radar chirp signal xx Performing Fourier transform to obtain a clutter power spectrum function P (f) of a background environment;
(4) And judging whether the clutter power spectral density function is updated by using an error comparator: establishing a clutter power spectrum function error comparator which comprises an environment updating mark e _ flag, a clutter power spectrum function error J, a clutter power spectrum function error threshold D, a clutter power spectrum function P (f) and a clutter power spectrum density pww (f), and judging whether the clutter power spectrum density of the background environment is updated or not by using the established clutter power spectrum function error comparator;
(5) Judging whether the waveform of the radar chirp signal is updated: if the environment updating flag e _ flag is 1, corresponding to clutter power spectrum function updating, the background environment is changed, the step (6) is executed, the optimal phase vector and the optimal radar transmitting waveform are solved, and the radar linear frequency modulation signal waveform is updated to the optimal radar transmitting waveform; if the environment updating flag e _ flag is not 1, the corresponding clutter power spectrum function is not updated, and the background environment is not changed, the radar linear frequency modulation signal waveform is not updated, and the current radar linear frequency modulation signal waveform is continuously maintained;
(6) Solving the optimal phase vector and the optimal radar emission waveform: firstly, theoretical Energy Spectral Density (ESD) of an optimal radar transmitting waveform is solved by utilizing clutter power spectral density pww (f), then, actual Energy Spectral Density (ESD) of the optimal radar transmitting waveform is introduced, a minimum mean square error function of the actual energy spectral density of the optimal radar transmitting waveform and the theoretical energy spectral density of the optimal radar transmitting waveform is established, phase iteration is carried out on the minimum mean square error function, and when the absolute value of the error function of two adjacent iterations is smaller than an iteration termination error threshold value, an optimal phase vector and the optimal radar transmitting waveform are obtained.
The invention is used for solving the technical problem of low accuracy of environment clutter estimation in the prior art
Compared with the prior art, the invention has the following advantages:
first, accuracy: according to the method, the clutter power spectrum density is obtained by processing and estimating the pulse echo data, real-time interaction and information acquisition of the radar working environment are realized, the clutter energy distribution characteristic under the current scene is accurately estimated, and the method has higher accuracy compared with the method for acquiring the environment clutter distribution characteristic from a radar environment library in the prior art.
Second, robustness: the invention adopts a clutter power spectrum function error comparison method to judge whether the clutter power spectrum density needs to be updated or not, further determines whether the radar transmitting waveform needs to be optimized or not, increases the overall robustness of the method, and reduces unnecessary operation amount.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a radar image of a scene without targets;
FIG. 3 is a time domain echo of a pulse;
FIG. 4 is a pulse-compressed one-dimensional range profile of a time-domain echo;
FIG. 5 is an autocorrelation function R of a one-dimensional range profile xx ；
FIG. 6 is a clutter power spectrum function P (f);
fig. 7 is the Energy Spectral Density (ESD) of the optimal transmit waveform of the present invention.
The specific implementation mode is as follows:
the invention is described in detail below with reference to the figures and specific embodiments.
Example 1
In 2005, the DARPA and navy research laboratories in the United states jointly develop a self-adaptive waveform design research project for detecting a low-ground-angle small RCS target in a complex marine environment, and the detection, resolution and tracking performances of the low-ground-angle small RCS target under a strong sea clutter condition are improved through real-time optimization of radar emission waveforms.
However, the waveform design method is only suitable for the condition that prior information is known or a radar environment database is established, and does not interact with the environment in real time to obtain required information, so that when the radar working scene environment changes complicatedly and is not in the known database, the improvement of the signal-to-noise ratio and the improvement of the detection performance cannot be guaranteed.
Aiming at the current situation, the invention develops the research of the optimized waveform design based on clutter power self-optimization. The problem of low accuracy is solved, and a waveform design method based on clutter power spectral density self-optimization is provided, referring to fig. 1, and the method comprises the following steps:
(1) Acquiring a one-dimensional range profile corresponding to each pulse containing clutter distribution information: by usingThe method comprises the steps of actually measuring a scene graph to be distributed, wherein clutter distribution characteristics of the scene are unknown, a radar linear frequency modulation signal is used for irradiating the scene without a target, the working bandwidth of a radar is B, echo imaging of the scene is shown in figure 2, the figure 2 is a two-dimensional image formed by irradiation of the radar on a flying area, and the scene is considered to contain clutter information of a target background environment. The method receives radar echo data under an actual measurement scene, wherein a time domain echo of one pulse is shown in figure 3, an abscissa is a time domain distance sampling unit, an ordinate is an echo amplitude of each distance unit, and the echo amplitude distribution of each distance unit in figure 3 does not show an obvious rule. And performing pulse compression processing on the real-time radar echo data to obtain one-dimensional range profiles of a plurality of radar chirp signals, namely obtaining the one-dimensional range profiles corresponding to each pulse containing clutter distribution information. One-dimensional range profile defining the current pulse is x = [ x ] 1 ,x 2 ,...,x m ] T ∈R N Wherein x is i The amplitude of the ith distance resolution unit is R is a real number, N is a total dimension of a vector space, N is a positive integer, m is a serial number of the vector space dimension, and m =1, 2.
(2) Solving an autocorrelation function R for a one-dimensional range profile x of a current pulse of a radar chirp signal xx Fig. 4 is a one-dimensional range profile of a current pulse of a radar chirp signal, fig. 4 is a one-dimensional range profile of a time-domain echo after pulse compression, an abscissa is a range sampling unit, an ordinate is an amplitude of each range sampling point after pulse pressure, fig. 5 is an autocorrelation function of the one-dimensional range profile, the abscissa is the range sampling unit, and the ordinate is a normalized autocorrelation amplitude.
(3) Obtaining a clutter power spectrum function P (f) of the background environment: autocorrelation function R for radar chirp signal xx Performing fourier transform to obtain a clutter power spectrum function P (f) of the background environment, as shown in fig. 6, where fig. 6 is the clutter power spectrum function P (f), the abscissa is a frequency domain sampling unit, and the ordinate is normalized power, it can be seen that the clutter power spectrum function is unevenly distributed in each sampling unit of the frequency domain.
(4) And judging whether the clutter power spectral density function is updated by using an error comparator: and establishing a clutter power spectrum function error comparator which comprises an environment updating mark e _ flag, a clutter power spectrum function error J, a clutter power spectrum function error threshold D, a clutter power spectrum function P (f) and a clutter power spectrum density pww (f), and judging whether the clutter power spectrum density of the background environment is updated or not by using the established clutter power spectrum function error comparator.
(5) Judging whether the waveform of the radar chirp signal is updated: if the environment updating flag e _ flag is 1, corresponding to clutter power spectrum function updating, the background environment is changed, the step (6) is executed, the optimal phase vector and the optimal radar transmitting waveform are solved, and the radar linear frequency modulation signal waveform is updated to the optimal radar transmitting waveform; and if the environment updating flag e _ flag is not 1, the corresponding clutter power spectrum function is not updated, and the background environment is not changed, the radar chirp signal waveform is not updated, and the current radar chirp signal waveform is continuously maintained.
(6) Solving the optimal phase vector and the optimal radar emission waveform: if the environment update flag e _ flag is 1, firstly, a theoretical Energy Spectral Density (ESD) of an optimal radar transmitting waveform is solved by utilizing a clutter power spectral density pww (f), the solved ESD is shown in fig. 7, fig. 7 is the Energy Spectral Density (ESD) of the optimal radar transmitting waveform of the invention, an abscissa is a frequency domain sampling unit, and an ordinate is the energy of each frequency domain sampling point, so that it can be seen that the frequency domain energy of the optimal radar transmitting waveform is 0 to 500, the distribution of 1200 to 2000 sampling points is low, and the distribution of 500 to 1200 sampling points is high, then, the actual Energy Spectral Density (ESD) of the optimal radar transmitting waveform is introduced, a minimum mean square error function of the actual energy spectral density of the optimal radar transmitting waveform and the theoretical energy spectral density of the optimal radar transmitting waveform is established, phase iteration is performed on the minimum mean square error function, and when the absolute value of the error function of two adjacent iterations is smaller than an optimal iteration termination error threshold, a phase vector and the optimal radar transmitting waveform are obtained.
According to the method, the clutter power spectrum density is obtained by processing and estimating the pulse echo data, real-time interaction and information acquisition of the radar working environment are realized, the clutter energy distribution characteristic under the current scene is accurately estimated, and the method has higher accuracy compared with the method for acquiring the environment clutter distribution characteristic from a radar environment library in the prior art.
The technical idea of the invention is as follows: the method comprises the steps of irradiating a background environment without a target by using a linear frequency modulation waveform, receiving echo data, performing pulse compression processing to obtain a one-dimensional range profile, solving an autocorrelation function of the one-dimensional range profile, performing Fourier transform on the autocorrelation function to obtain an estimated value of a clutter power spectrum function, determining the clutter power spectrum function matched with the current environment through the constraint of a mean square error threshold value of the clutter power spectrum function obtained through estimation, and finally solving an optimal waveform time domain signal through a phase iteration method to realize the design of an optimal waveform adaptive to the current environment in real time.
Example 2
In 2012, a cognitive transmitting signal and receiving filter joint optimization algorithm based on constant modulus and similarity constraint is provided for a strong reflection clutter environment by a.Aubry and the like of Naples fredrick university Italy, and a radar system is assumed to comprise an environment knowledge base which comprises a geographic information system, a clutter scattering and spectrum model, meteorological information, a digital topographic map and the like, so that prior information such as a clutter map and a clutter spectrum model can be provided for a cognitive algorithm. However, the algorithm is only suitable for the condition that prior information is known or a radar environment database is established, and when the radar working scene environment changes complexly and is not in the known database, the accuracy and the detection performance of the algorithm cannot be improved.
In view of the above, the invention develops the research of the optimized waveform design based on clutter power self-optimization. Similar to embodiment 1, the method for designing a waveform based on clutter power spectral density self-optimization in step (4) of the present invention uses an error comparator to determine whether a clutter power spectral density function is updated, and specifically includes the following steps:
(4a) If the echo data of the first pulse is received, the comparator is considered not to store the clutter power spectrum function corresponding to the current pulse, the clutter power spectrum function P (f) is assigned to the clutter power spectrum density pww (f), and the environment updating flag e _ flag is set to be 1.
(4b) And setting a clutter power spectrum function error threshold D, wherein the clutter power spectrum function error threshold D is determined according to an empirical value which is generally 0.01 times of the sum of the clutter power spectrum values.
(4c) Calculating the error J between the current pulse and the pww (f) corresponding to the previous pulse: and calculating the error J between P (f) corresponding to the current pulse and pww (f) corresponding to the previous pulse by using a defined clutter power spectrum function error formula.
(4d) Judging whether the current environment clutter power spectrum function is updated: if the clutter power spectrum function error J is smaller than the threshold value D, the current environment clutter power spectrum function is not changed, pww (f) is not updated, and an environment updating flag e _ flag is set to be zero; and if the clutter power spectrum function error J is larger than the threshold value D, the current environment clutter power spectrum function is considered to be changed, pww (f) is updated, an updating formula is pww (f) = P (f), and an environment updating mark e _ flag is set to be 1.
Advantages of the summary
The error comparator can update the clutter power spectrum function of the current environment, accurately estimate the clutter energy distribution characteristic of the current scene, update the radar emission waveform and improve the accuracy. The error comparator is provided with a clutter power spectrum function error J and a clutter power spectrum function error threshold D, wherein the clutter power spectrum function error threshold D is determined according to an empirical value, the clutter power spectrum function is updated only when the clutter power spectrum function error J is smaller than the threshold D, and whether a radar transmitting waveform is updated is further judged, so that unnecessary operation is reduced, and the robustness of the whole method is improved.
Example 3
The waveform design method based on clutter power spectral density self-optimization is the same as the embodiment 1-2, and the clutter power spectral function error formula defined in the step (4 c) is as follows:
where B is the chirp bandwidth, pww (f) is the clutter power spectral density estimated for the previous pulse, and P (f) is the clutter power spectral function corresponding to the current pulse.
Advantages of the summary
The clutter power spectrum function error formula defined in the error comparator can calculate the error between P (f) corresponding to the pre-pulse and pww (f) corresponding to the pre-pulse, and when the error is greater than the clutter power spectrum function error threshold, the clutter power spectrum function is updated, so that the robustness of the whole method can be increased.
In 2018, luzhu of electronics science and technology university provides a waveform design algorithm based on environment spectrum knowledge in his doctor paper, and the method mainly improves the detection performance of the radar in a spectrum crowded environment from the aspect of optimizing the waveform design of a radar transmitting end through the environment spectrum knowledge in a radar environment knowledge base constructed previously. However, the method is to carry out the optimization design of the radar transmitting waveform on the premise that the radar environment knowledge base is known, and the optimization design of the radar transmitting waveform cannot be carried out on the condition that the environment knowledge is unknown. The optimal waveform design based on clutter power self-optimization realizes real-time interaction and information acquisition of the radar working environment, and improves the radar detection performance.
A more detailed example is given below to further illustrate the invention
Example 4
The same wave form design method based on clutter power spectral density self-optimization as the embodiment 1-3, referring to fig. 1, the invention includes the following steps
(1) Acquiring a one-dimensional range profile corresponding to each pulse containing clutter distribution information: the method comprises the steps of using an actually measured scene graph to perform point distribution, wherein clutter distribution characteristics of the scene are unknown, using radar chirp signals to irradiate the scene without a target, enabling a working bandwidth to be B, enabling echo imaging of the scene to be shown in figure 2, enabling the scene to be a two-dimensional image formed by irradiation of a radar on a flying area, considering that the scene comprises clutter information of a target background environment, receiving radar echo data in the scene, enabling a time domain echo of one pulse to be shown in figure 3, enabling a horizontal coordinate to be a time domain distance sampling unit, enabling a vertical coordinate to be echo amplitudes of each distance unit, and enabling echo amplitude distribution of each distance unit in figure 3 not to show obvious rules. For real-time radar echoPerforming pulse compression processing on the data to obtain one-dimensional range profiles of a plurality of radar linear frequency modulation signals, namely acquiring the one-dimensional range profile corresponding to each pulse containing clutter distribution information; define the one-dimensional range profile of the current pulse as x = [ x ] 1 ,x 2 ,...,x m ] T ∈R N Wherein x is i For the amplitude of the i-th resolution unit, R is a real number, N is a total dimension of the vector space, N is a positive integer, m is a serial number of the vector space dimension, m =1, 2.
(2) Solving an autocorrelation function R for a one-dimensional range profile x of a current pulse of a radar chirp signal xx The one-dimensional range profile of the current pulse of the radar chirp signal is shown in fig. 4, fig. 4 is the one-dimensional range profile of the time domain echo after pulse compression, the abscissa is a range sampling unit, the ordinate is the amplitude of each range sampling point after pulse compression, the autocorrelation function of the one-dimensional range profile is shown in fig. 5, the abscissa is the range sampling unit, and the ordinate is normalized autocorrelation amplitude.
(3) For the autocorrelation function R xx Performing fourier transform, as shown in fig. 6, to obtain a clutter power spectrum function P (f) of the background environment, where fig. 6 is the clutter power spectrum function P (f), the abscissa is a frequency domain sampling unit, and the ordinate is normalized power, and it can be seen that the clutter power spectrum function is unevenly distributed in each sampling unit of the frequency domain.
(4) And judging whether the clutter power spectral density function is updated by using an error comparator: establishing a clutter power spectrum function error comparator, wherein the error comparator comprises an environment updating mark e _ flag, a clutter power spectrum function error J, a clutter power spectrum function error threshold D, a clutter power spectrum function P (f) and a clutter power spectrum density pww (f), and judging whether the clutter power spectrum density of the background environment is updated by using the constructed clutter power spectrum function error comparator:
(4a) If the echo data of the first pulse is received, the comparator is considered not to store the clutter power spectrum function corresponding to the current pulse, the clutter power spectrum function P (f) is assigned to the clutter power spectrum density pww (f), and the environment updating flag e _ flag is set to be 1.
(4b) And setting a clutter power spectrum function error threshold D.
(4c) Calculating the error J between pww (f) corresponding to the current pulse and the previous pulse: and calculating the error J between P (f) corresponding to the current pulse and pww (f) corresponding to the previous pulse by using a defined clutter power spectrum function error formula.
(4d) Judging whether the current environment clutter power spectrum function is updated: if the clutter power spectrum function error J is smaller than the threshold value D, the current environment clutter power spectrum function is not changed, pww (f) is not updated, and an environment updating flag e _ flag is set to be zero; and if the clutter power spectrum function error J is larger than the threshold value D, the current environment clutter power spectrum function is considered to be changed, pww (f) is updated, an updating formula is pww (f) = P (f), and an environment updating mark e _ flag is set to be 1.
(5) Judging whether the waveform of the radar chirp signal is updated: if the environment updating flag e _ flag is 1, corresponding to the update of the clutter power spectrum function, the background environment is changed, the step (6) is executed, the actual optimal phase vector and the optimal radar transmitting waveform are solved, and the radar linear frequency modulation signal waveform is updated to the optimal radar transmitting waveform; if the environment updating flag e _ flag is not 1, the corresponding clutter power spectrum function is not updated, and the background environment is not changed, the radar linear frequency modulation signal waveform is not updated, and the current radar linear frequency modulation signal waveform is continuously maintained;
(6) Solving the actual optimal phase vector and the optimal transmitting waveform: if the environment updating flag e _ flag is 1, firstly, theoretical Energy Spectrum Density (ESD) of an optimal radar transmitting waveform is solved by utilizing clutter power spectrum density pww (f), then, actual energy spectrum density of the optimal radar transmitting waveform is defined, then, a minimum mean square error function of the optimal radar transmitting waveform theoretical ESD and the optimal radar transmitting waveform actual ESD is established, and finally, an actual optimal phase vector and an optimal radar transmitting waveform are solved by utilizing a phase iteration method. Can be specifically described as the following steps
6a) The signal-to-noise ratio is taken as a standard rule function, the finite property of constant envelope and energy of a signal is taken as a constraint condition, the noise is considered to be a generalized stable Gaussian process, and the theoretical Energy Spectral Density (ESD) of the optimal radar emission waveform is solved to be
In the formula P nn (f) In order to obtain noise power spectral density, λ is constant, the solved ESD is shown in fig. 7, fig. 7 is Energy Spectral Density (ESD) of the optimal radar transmission waveform of the present invention, the abscissa is frequency domain sampling unit, and the ordinate is energy of each frequency domain sampling point, it can be seen that frequency domain energy of the optimal transmission waveform is in 0 to 500, and 1200 to 2000 sampling points are distributed lower, and 500 to 1200 sampling points are distributed higher, and actual energy spectral density of the introduced optimal radar transmission waveform is
Wherein u is the actual radar transmitting waveform and e is the natural index.
6b) Establishing a minimum mean square error function of an optimal radar transmitting waveform theory ESD and an optimal radar transmitting waveform actual ESD
6c) Initializing a phase vector
And the iteration number p =0, calculating the ESD error G of the first iteration (0) 。
6d) The number of iterations flag p = p + 1.
6e) Sequentially increasing k from 1 to N-1, solving minimum value points of functions according to the condition that a first derivative is equal to zero and a second derivative is greater than zero
And
of two conditions
Obtaining the optimal phase vector under the iteration after k is increased progressively
6f) Substituting the newly solved phase vector into the time domain signal
Updating ESD error cost function
Calculating the absolute value delta = | G between the ESD error function and the last ESD error function under the iteration (p) -G (p-1) |。
6g) If delta is larger than delta and delta is a given iteration termination error threshold value, returning to the step 2 for continuing iteration, if delta is smaller than delta, terminating iteration, and finally obtaining a phase vector by iteration times
For the optimal phase vector, the optimal radar transmitting waveform is designed as
c is the transmitted signal amplitude determined by the transmitted signal energy E together with the signal duration T.
In summary, the waveform design method based on clutter power spectral density self-optimization provided by the invention solves the technical problems of low environmental clutter estimation accuracy and low real-time performance in the prior art. The implementation steps are as follows: irradiating a scene, receiving radar echo data, and performing pulse compression processing to obtain a one-dimensional range profile; solving an autocorrelation function of the one-dimensional range profile, and performing Fourier transform on the autocorrelation function to obtain a clutter power spectrum function; comparing the obtained clutter power spectrum function with the clutter power spectrum function of the previous pulse to determine an environment updating mark and a final clutter power density; and judging the environment updating mark, and solving the phase of the optimal waveform by adopting a phase iteration method. The method estimates the clutter power spectrum density of the environment in real time, makes full use of the environment information, reduces unnecessary calculation by a clutter function error comparison method, effectively improves the signal-to-noise-and-noise ratio of the received signal, and improves the radar target detection performance.
Claims (3)
1. A waveform design method based on clutter power spectral density self-optimization is characterized by comprising the following steps:
(1) Acquiring a one-dimensional range profile corresponding to each pulse containing clutter distribution information:
irradiating a scene without a target by using a radar linear frequency modulation signal, wherein the scene is considered to contain clutter information of a target background environment; receiving radar echo data in the scene, and performing pulse compression processing on the real-time radar echo data to obtain one-dimensional range profiles of a plurality of radar linear frequency modulation signals; define the one-dimensional range profile of the current pulse as x = [ x ] 1 ,x 2 ,...,x m ] T ∈R N Wherein x is i The amplitude of the ith distance resolution unit is shown, R is a real number, N is a total dimension of a vector space, N is a positive integer, m is a serial number of the vector space dimension, m =1, 2.
(2) Solving an autocorrelation function R for a one-dimensional range profile x of a current pulse of a radar chirp signal xx ；
(3) Obtaining a clutter power spectrum function P (f) of the background environment: autocorrelation function R for radar chirp signal xx Performing Fourier transform to obtain a clutter power spectrum function P (f) of a background environment;
(4) And judging whether the clutter power spectral density function is updated by using an error comparator: establishing a clutter power spectrum function error comparator which comprises an environment updating mark e _ flag, a clutter power spectrum function error J, a clutter power spectrum function error threshold D, a clutter power spectrum function P (f) and a clutter power spectrum density pww (f), and judging whether the clutter power spectrum density of the background environment is updated or not by using the established clutter power spectrum function error comparator;
(5) Judging whether the waveform of the radar chirp signal is updated: if the environment updating flag e _ flag is 1, corresponding to clutter power spectrum function updating, the background environment is changed, the step (6) is executed, the optimal phase vector and the optimal radar transmitting waveform are solved, and the radar linear frequency modulation signal waveform is updated to the optimal radar transmitting waveform; if the environment updating flag e _ flag is not 1, the corresponding clutter power spectrum function is not updated, and the background environment is not changed, the radar linear frequency modulation signal waveform is not updated, and the current radar linear frequency modulation signal waveform is continuously maintained;
solving the optimal phase vector and the optimal radar emission waveform: firstly, theoretical energy spectral density of an optimal radar transmitting waveform is solved by utilizing clutter power spectral density pww (f), then, actual Energy Spectral Density (ESD) of the optimal radar transmitting waveform is introduced, a minimum mean square error function of the actual energy spectral density of the optimal radar transmitting waveform and the theoretical energy spectral density of the optimal radar transmitting waveform is established, phase iteration is carried out on the minimum mean square error function, and when the absolute value of the error function of two adjacent iterations is smaller than an iteration termination error threshold value, an optimal phase vector and the optimal radar transmitting waveform are obtained.
2. The clutter power spectral density self-optimizing waveform design method of claim 1, wherein: the step (4) of determining whether the clutter power spectral density function is updated by using the error comparator specifically includes the following steps:
(4a) If the echo data of the first pulse is received, the comparator is considered to have no clutter power spectrum function corresponding to the current pulse stored, the clutter power spectrum function P (f) is assigned to the clutter power spectrum density pww (f), and an environment updating mark e _ flag is set to be 1;
(4b) Setting a clutter power spectrum function error threshold D;
(4c) Calculating the error J between the current pulse and the pww (f) corresponding to the previous pulse: calculating an error J between P (f) corresponding to the current pulse and pww (f) corresponding to the previous pulse by using a defined clutter power spectrum function error formula;
(4d) Judging whether the current environment clutter power spectrum function is updated: if the clutter power spectrum function error J is smaller than the threshold value D, the current environment clutter power spectrum function is considered to be unchanged, pww (f) is not updated, and an environment updating flag e _ flag is set to be zero; and if the clutter power spectrum function error J is larger than the threshold value D, the current environment clutter power spectrum function is considered to be changed, pww (f) is updated, an updating formula is pww (f) = P (f), and an environment updating mark e _ flag is set to be 1.
3. The clutter power spectral density self-optimizing waveform design method of claim 2, wherein: the clutter power spectrum function error formula defined in the step (4 c) is as follows:
where B is the chirp bandwidth, pww (f) is the clutter power spectral density estimated for the previous pulse, and P (f) is the clutter power spectral function corresponding to the current pulse.
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