Cognitive radar constant modulus waveform design method and device based on maximizing signal-to-jamming-and-noise ratio

Abstract

The embodiment of the application relates to the technical field of cognitive radar, and provides a cognitive radar constant modulus waveform design method and device based on maximum signal-to-clutter-noise ratio, the method comprising: obtaining a feedback signal echo obtained after a cognitive radar transmitting signal, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component is output after the transmitting signal is convolved with a unit impulse response of a target, and the clutter echo component is output after the transmitting signal is reflected by a clutter scattering point; calculating a signal-to-clutter-noise ratio of an output signal after a matched filter based on the feedback signal echo; obtaining an optimal energy spectrum density of the transmitting signal when the signal-to-clutter-noise ratio is maximum under a preset energy constraint condition; and determining a target constant modulus signal waveform based on the optimal energy spectrum density. Therefore, the radar waveform is dynamically adjusted through the interaction between the radar and the environment, better adaptability is achieved in a complex clutter environment, the balance between time domain and frequency domain characteristics is maintained, and target detection performance is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cognitive radar and radar waveform design, in particular to a cognitive radar constant modulus waveform design method and device based on maximum signal-to-clutter-plus-noise ratio. BACKGROUND

[0002] Traditional radars usually transmit fixed waveforms (such as linear frequency modulation waveforms, pulse waveforms, etc.). However, these waveforms have limitations in a dynamic complex electromagnetic environment (such as strong clutter, interference, noise, etc.), and cannot be adaptively adjusted according to real-time environmental changes.

[0003] In recent years, cognitive radar technology has become a research hotspot. Its core idea is to enable the radar system to perceive the changes in the external environment in real time through a feedback mechanism, and dynamically adjust the radar waveform based on the perceived information, so as to obtain better detection performance in a complex environment. For the problem of target detection in a clutter background, the goal of waveform design is to maximize the receiver output signal-to-clutter-plus-noise ratio (SCNR), thereby improving the performance of target detection. The environmental information at this time is the background clutter signal, which is brought into the expression of SCNR, and the frequency domain response of the optimal waveform can be solved, and then the time domain transmitting waveform is synthesized. In the frequency domain response design stage, the water filling method is generally used for waveform energy allocation to reduce the influence of clutter on target detection; in the time domain waveform synthesis stage, the widely used methods at present are iterative algorithms such as Durbin method, interior point method, etc.

[0004] In the process of maximizing the signal-to-clutter-plus-noise ratio, some methods can only obtain the energy spectral density (ESD) of the optimal waveform. To obtain the time domain signal, further time domain waveform synthesis is required. In the time domain signal synthesis stage, the existing methods are as follows:

[0005] The Durbin method is a method for synthesizing time domain signals, which is usually used in Moving Average model (MA) spectrum estimation. Its characteristic is that the synthesized signal is a minimum phase signal. First, the expected ESD is subjected to Fourier inverse transform to obtain the autocorrelation function of the target time domain signal. The best linear prediction coefficient can be obtained by using the Levinson algorithm, and the MA coefficient is obtained by substituting the autocorrelation function into the Yule Walker equation, which is the time domain waveform to be designed. This method does not consider the length of the time domain signal, and cannot achieve the design goal under the constraints of constant modulus and peak-to-average power ratio.

[0006] Another method is to synthesize the time-domain signal based on the principle of stationary phase. The core idea is that when the phase changes sharply, only the area where the phase changes slowly has a significant contribution to the integral. Specifically, the stationary phase method finds the stationary points in the integral (i.e., the points where the phase derivative is zero), and the contribution near these points is much greater than other areas, so the integral value can be approximated. By calculating the known energy spectrum signal, the group delay function of the signal can be obtained , and the frequency modulation function of the signal can be obtained by taking the inverse function of the group delay, and then the phase of the signal can be obtained. Although the time-domain length of the transmitted signal can be controlled, the effectiveness of the stationary phase method depends on the rapid change of the phase function, so the accuracy of this method will decrease significantly in the case of low frequency or slow phase change. If the frequency of the signal is low or the phase change is not sharp enough, the stationary phase method may not provide an effective approximation.

[0007] In practical applications, the synthesized time-domain signal often needs to satisfy the constant modulus constraint, which is to ensure that the nonlinear power amplifier remains in the high-efficiency operating interval, reduces nonlinear distortion, and thus improves the energy utilization of the system. At the same time, the constant modulus signal has uniform energy distribution in the transmission process, reducing the dependence on signal amplitude modulation and enhancing the anti-interference performance of the radar signal in complex environments, which is beneficial to target detection. The existing technology still faces great challenges in accurately synthesizing optimal waveforms that satisfy both time-domain and frequency-domain constraints, especially in achieving constant envelope and optimizing ESD consistency. SUMMARY

[0008] The present application provides a cognitive radar constant modulus waveform design method and device based on maximizing the signal-to-clutter ratio, to solve the limitations of existing cognitive radar in complex environments, the inability to adaptively adjust according to real-time environmental changes, and to achieve better adaptability in complex clutter environments, while maintaining the balance between time-domain and frequency-domain characteristics to improve target detection performance.

[0009] The present application provides a cognitive radar constant modulus waveform design method based on maximizing the signal-to-clutter ratio, comprising:

[0010] Obtain the feedback signal echo after obtaining the cognitive radar transmitted signal, wherein the feedback signal echo includes target echo components and clutter echo components, the target echo components are the output after the transmitted signal is convolved with the unit impulse response of the target, and the clutter echo components are the output after the transmitted signal is reflected by the clutter scattering point;

[0011] Calculate the signal-to-clutter ratio of the output signal after the matched filter based on the feedback signal echo;

[0012] Under the preset energy constraint condition, obtain the optimal energy spectrum density of the transmitted signal when the signal-to-clutter ratio is maximum.

[0013] determining a target constant modulus signal waveform based on the optimal energy spectral density.

[0014] In a possible implementation, the method further includes:

[0015] inputting the feedback signal echo into a preset signal transmission system model, and calculating a signal-to-jamming-and-noise ratio of an output signal through a linear convolution operation of a filter.

[0016] In a possible implementation, the method further includes:

[0017] adopting a Lagrange multiplier method to design the energy spectral density of the transmission signal;

[0018] under a preset energy constraint condition, optimizing the signal-to-jamming-and-noise ratio of the transmission signal at any moment with the maximum signal-to-jamming-and-noise ratio as a target;

[0019] obtaining an optimal energy spectral density of the transmission signal when the signal-to-jamming-and-noise ratio is maximum.

[0020] In a possible implementation, the method further includes:

[0021] based on a preset constant modulus constraint condition, projecting any signal waveform into a signal set and a constant modulus signal set with the same frequency domain characteristics as the optimal energy spectral density through an alternating projection algorithm for iteration;

[0022] based on a preset number of iterations, obtaining a target constant modulus signal waveform with a similarity between a frequency energy spectral density and the optimal energy spectral density greater than a threshold value.

[0023] In a possible implementation, the method further includes:

[0024] based on a preset constant modulus constraint condition, selecting a signal waveform set through an alternating projection algorithm to gradually reduce an error between any signal waveform in the signal waveform set and a target waveform in energy spectral density.

[0025] In a possible implementation, the method further includes:

[0026] detecting a target again by transmitting the target constant modulus signal waveform through the cognitive radar;

[0027] obtaining a feedback signal echo obtained after transmitting the target constant modulus signal waveform, and performing the step of calculating the signal-to-jamming-and-noise ratio of the output signal after the matched filter based on the feedback signal echo.

[0028] The application also provides a cognitive radar constant modulus waveform design device based on maximum signal-to-jamming-and-noise ratio, including the following modules:

[0029] an acquisition module configured to acquire a feedback signal echo obtained after a cognitive radar transmits a signal, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component being an output after the transmitted signal is convolved with a unit impulse response of a target, and the clutter echo component being an output after the transmitted signal is reflected by a clutter scattering point;

[0030] a design module configured to calculate a signal-to-clutter-plus-noise ratio of an output signal after a matched filter based on the feedback signal echo;

[0031] The design module is further configured to acquire an optimal energy spectral density of the transmitted signal when the signal-to-clutter-plus-noise ratio is maximum under a preset energy constraint condition.

[0032] A determination module is configured to determine a target constant modulus signal waveform based on the optimal energy spectral density.

[0033] The application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the cognitive radar constant modulus waveform design method based on maximum signal-to-clutter-plus-noise ratio according to any one of the above.

[0034] The application further provides a non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program is executable on a processor to implement the cognitive radar constant modulus waveform design method based on maximum signal-to-clutter-plus-noise ratio according to any one of the above.

[0035] The application further provides a computer program product comprising a computer program, wherein the computer program is executable on a processor to implement the cognitive radar constant modulus waveform design method based on maximum signal-to-clutter-plus-noise ratio according to any one of the above.

[0036] The present invention provides a cognitive radar constant-mode waveform design method and apparatus based on maximizing signal-to-clutter-to-noise ratio (SNR). This method involves acquiring the feedback signal echo obtained after the cognitive radar transmits a signal. The feedback signal echo includes a target echo component and a clutter echo component. The target echo component is the output of the convolution of the transmitted signal and the target's unit impulse response. The clutter echo component is the output of the transmitted signal after reflection from a clutter scattering point. The method calculates the SNR of the output signal after passing through a matched filter based on the feedback signal echo. Under a preset energy constraint, it obtains the optimal energy spectral density of the transmitted signal when the SNR is maximized. Finally, it determines the target constant-mode signal waveform based on the optimal energy spectral density. Compared to existing cognitive radar technologies, which have limitations in complex environments and cannot adaptively adjust to real-time environmental changes, this solution dynamically adjusts the radar waveform through interaction between the radar and the environment. In the time-domain signal synthesis stage, it not only considers the energy constraints in the frequency domain but also introduces constant mode constraints. It uses an alternating projection algorithm to synthesize the time-domain waveform, ensuring that the amplitude of the transmitted waveform is constant, which helps to reduce the nonlinear distortion of the amplifier. It has better adaptability in complex clutter environments, maintains a balance between time-domain and frequency-domain characteristics, and improves target detection performance. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0038] Figure 1 This is one of the flowcharts of the cognitive radar constant mode waveform design method based on maximizing the signal-to-clutter-to-noise ratio provided by the present invention.

[0039] Figure 2 This is the second flowchart of the cognitive radar constant mode waveform design method based on maximizing the signal-to-clutter-to-noise ratio provided by the present invention.

[0040] Figure 3 This is the third flowchart of the cognitive radar constant mode waveform design method based on maximizing the signal-to-clutter-to-noise ratio provided by the present invention.

[0041] Figure 4 This is a schematic diagram of the signal transmission system model provided by the present invention.

[0042] Figure 5 This is a schematic diagram comparing the energy spectral density of the target constant-mode signal waveform and the desired energy spectral density provided by the present invention.

[0043] Figure 6Is the feedback signal echo schematic diagram corresponding to the transmitted signal provided by the application.

[0044] Figure 7 Is the feedback signal echo schematic diagram corresponding to the optimized target constant modulus signal waveform provided by the application.

[0045] Figure 8 Is the structural schematic diagram of the cognitive radar constant modulus waveform design device based on the maximum signal-to-clutter ratio provided by the application.

[0046] Figure 9 Is the structural schematic diagram of the electronic device provided by the application. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the present application will be described clearly and completely in combination with the drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0048] In order to facilitate the understanding of the embodiments of the present application, the following will be further explained and described in specific embodiments in combination with the drawings, and the embodiments do not constitute a limitation on the embodiments of the present application.

[0049] Figure 1 Is one of the flowcharts of the cognitive radar constant modulus waveform design method based on the maximum signal-to-clutter ratio provided by the application, as shown in the figure, the method specifically includes: Figure 1

[0050] S11, the feedback signal echo obtained after acquiring the transmitted signal of the cognitive radar.

[0051] The embodiment of the present application proposes a two-step waveform design method, which aims to realize the constant modulus waveform design of the maximum signal-to-clutter ratio. The method includes an energy spectrum density (ESD) design stage and a time-domain constant modulus signal design stage, as shown in the figure. Figure 3

[0052] ​​In the embodiment of the present application, a constant modulus constraint is introduced in the adaptive radar waveform design to realize the constant modulus waveform design of maximum signal-to-clutter-plus-noise ratio (SCNR). In the optimal ESD design stage, the signal energy is distributed to the frequency band with small clutter component and large target component by the water-filling method, which can effectively improve the SCNR in target detection. In the design stage of the time-domain signal, the constant modulus waveform satisfying the optimal ESD condition needs to be solved. This problem belongs to the phase retrieval problem, and the core challenge is how to effectively convert between the frequency domain and the time domain while satisfying two key conditions: one is that the time-domain waveform must have a constant envelope, and the other is that the error between the energy spectrum density in the frequency domain and the given optimal ESD is minimized. Therefore, the alternating projection algorithm is introduced to gradually reduce the error between the design waveform and the target waveform in the ESD by projecting the design signal to the template, and finally obtain the waveform satisfying the time-domain constant envelope constraint and the minimum ESD error in the frequency domain.

[0053] Specifically, first, a target detection signal is transmitted by a cognitive radar, and then a feedback signal echo is obtained after the transmitted signal. The feedback signal echo includes a target echo component and a clutter echo component; the target echo component is the output after the transmitted signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmitted signal is reflected by the clutter scattering point.

[0054] S12, calculate the signal-to-clutter-plus-noise ratio of the output signal after the matched filter based on the feedback signal echo.

[0055] The embodiment of the present application pre-establishes a signal transmission system model in a single-transmit-single-receive system, and regards the target echo component and the clutter echo component in the feedback signal echo as the outputs after the transmitted signal passes through a linear system. The signal-to-clutter-plus-noise ratio at any time of the transmitted signal is calculated through the linear convolution operation of the filter in the signal transmission system model.

[0056] S13, obtain the optimal energy spectrum density of the transmitted signal when the signal-to-clutter-plus-noise ratio is maximum under the preset energy constraint condition.

[0057] Then, the energy limited energy spectrum density design is performed: the signal energy spectrum density design is performed by using the Lagrange multiplier method, and the energy spectrum density expression of the transmitted signal is determined by solving the maximum value of the Lagrange function. Further, the signal-to-clutter-plus-noise ratio at any time of the transmitted signal is optimized with the maximum signal-to-clutter-plus-noise ratio as the target under the preset energy constraint condition; and the optimal energy spectrum density of the transmitted signal when the signal-to-clutter-plus-noise ratio is maximum is obtained.

[0058] S14, determine the target constant modulus signal waveform based on the optimal energy spectrum density.

[0059] Finally, the time-domain constant modulus signal design is performed: the amplitude of the transmitted signal is set as a constant value A, and the phase sequence is randomly generated. The time-domain generated constant modulus signal is projected into a signal set having the same frequency domain characteristics as the optimal energy spectrum density by using an alternating projection algorithm to obtain a projected signal. The projected signal is transformed into the time domain, the phase is kept unchanged, and the amplitude is modified as A to complete an iteration process. The iteration process is repeated until the frequency domain characteristics of the obtained constant modulus signal match the expected energy spectrum density to obtain the target constant modulus signal waveform.

[0060] The target is detected again by transmitting the target constant modulus signal waveform by the cognitive radar. The feedback signal echo obtained after transmitting the target constant modulus signal waveform is further subjected to the maximum signal-to-clutter-and-noise ratio cognitive radar constant modulus waveform design step.

[0061] The embodiment of the present application dynamically adjusts the radar waveform through the interaction between the radar and the environment, which is different from the frequency energy constraint in the traditional waveform design. In the time-domain waveform synthesis, not only the frequency domain energy constraint is considered, but also the constant modulus constraint is introduced. The time-domain waveform synthesis is realized by using the alternating projection algorithm. The amplitude of the transmitted waveform is ensured to be constant, which helps to reduce the nonlinear distortion of the amplifier and improve the detection accuracy.

[0062] The method for designing a constant modulus waveform of a cognitive radar based on maximum signal-to-clutter-and-noise ratio provided by the present application comprises the following steps: obtaining a feedback signal echo after transmitting a signal of the cognitive radar, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component is an output after the transmitted signal is convolved with a unit impulse response of a target, and the clutter echo component is an output after the transmitted signal is reflected by a clutter scattering point; calculating a signal-to-clutter-and-noise ratio of an output signal after a matched filter based on the feedback signal echo; obtaining an optimal energy spectrum density of the transmitted signal when the signal-to-clutter-and-noise ratio is maximum under a preset energy constraint condition; and determining a target constant modulus signal waveform based on the optimal energy spectrum density. Compared with the existing technology, the cognitive radar has limitations in a complex environment and cannot be adaptively adjusted according to real-time environmental changes. By the method, the radar waveform is dynamically adjusted through the interaction between the radar and the environment. In the time-domain signal synthesis stage, not only the frequency domain energy constraint is considered, but also the constant modulus constraint is introduced. The time-domain waveform synthesis is realized by using the alternating projection algorithm. The amplitude of the transmitted waveform is ensured to be constant, which helps to reduce the nonlinear distortion of the amplifier. In a complex clutter environment, the method has better adaptability, keeps the balance between the time domain and the frequency domain characteristics, and improves the target detection performance.

[0063] Figure 2 is a flowchart of the method for designing a constant modulus waveform of a cognitive radar based on maximum signal-to-clutter-and-noise ratio provided by the present application, as shown in Figure 2 The method specifically comprises the following steps:

[0064] S21, obtaining the feedback signal echo obtained after the cognitive radar transmits a signal.

[0065] Embodiments of the present application propose a two-step waveform design method, aiming to realize constant modulus waveform design that maximizes the signal-to-clutter-plus-noise ratio. The method includes an energy spectral density (ESD) design stage and a time-domain constant modulus signal design stage, as shown in Figure 3 .

[0066] In embodiments of the present application, a constant modulus constraint is introduced in adaptive radar waveform design, realizing constant modulus waveform design that maximizes the signal-to-clutter-plus-noise ratio (SCNR). In the optimal ESD design stage, by using the water-filling method, the signal energy is distributed to the frequency band where the clutter component is small and the target component is large, which can effectively improve the SCNR in target detection. In the design stage of the time-domain signal, the constant modulus waveform that satisfies the optimal ESD condition needs to be solved. This problem belongs to the phase retrieval problem, and the core challenge is how to effectively convert between the frequency domain and the time domain while satisfying two key conditions: one is that the time-domain waveform must have a constant envelope, and the other is that the error between the energy spectral density in the frequency domain and the given optimal ESD is minimized. Therefore, the alternating projection algorithm is introduced, which gradually reduces the error between the design waveform and the target waveform in ESD by projecting the design signal to the template, and finally obtains the waveform that satisfies the time-domain constant envelope constraint and has the minimum ESD error in the frequency domain.

[0067] Specifically, first, a target detection signal is transmitted by a cognitive radar, and then a feedback signal echo obtained after the transmitted signal is acquired. The feedback signal echo includes a target echo component and a clutter echo component; the target echo component is the output after the transmitted signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmitted signal is reflected by the clutter scattering point.

[0068] S22, inputting the feedback signal echo into a preset signal transmission system model, and calculating the signal-to-clutter-plus-noise ratio of the output signal through linear convolution operation of the filter.

[0069] Embodiments of the present application pre-establish a signal transmission system model in a single-transmit-single-receive system, as shown in Figure 4 The target echo component and the clutter echo component in the feedback signal echo are respectively regarded as the output after the transmitted signal passes through the linear system and. The signal-to-clutter-plus-noise ratio of the output signal is calculated through the linear convolution operation of the filter in the signal transmission system model.

[0070] Specifically, the one-time transmitted signal waveform is The target echo component and the clutter echo component in the echo are respectively regarded as the output after the transmitted signal After passing through a linear system and , the output, both target and clutter unit impulse response, respectively. At the receiving end, the echo enters the filter with additive noise, and the output is .

[0071] Let the filter input signal be , then we have:

[0072]

[0073] where * represents linear convolution operation, can be represented as the superposition of several different time delay impulse signals, each of which represents a target reflection point on a distance unit (the embodiment of the present application adopts point target, i.e. ), is noise. After passing through the filter, the signal is:

[0074]

[0075] At time t, the SCNR of the output signal can be represented as:

[0076]

[0077] Transformed into frequency domain form:

[0078]

[0079] where are the energy spectral densities of the clutter and noise, respectively, and others are the Fourier Transform (FT) of the corresponding responses. Let . According to the Cauchy-Schwarz inequality, the SCNR can be scaled as:

[0080]

[0081] It can be seen that when the filter satisfies: , the equality holds. Considering that the frequency range of the transmitted signal in the actual radar system is , where B is the bandwidth of the transmitted signal, and the signal is a constant modulus signal with a time domain amplitude of A. Then the final optimization problem can be transformed into:

[0082]

[0083] S23, the energy spectral density of the transmitted signal is designed by using the Lagrange multiplier method.

[0084] S24. Under a preset energy constraint, optimize the signal-to-noise ratio (SNR) of the transmitted signal at any time with the goal of maximizing the SNR.

[0085] Energy-Limited Energy Spectral Density (ESD) Design: The signal energy spectral density is designed using the Lagrange multiplier method. The ESD expression of the transmitted signal is determined by solving for the maximum value of the Lagrange function. Then, under the preset energy constraint, the signal-to-clutter-to-noise ratio (SCR) is optimized with the goal of maximizing the SCR.

[0086] Specifically, for energy constraints, the Lagrange multiplier method can be used to design the signal energy spectral density. Let the Lagrange multipliers be... Then the Lagrange function can be written as:

[0087]

[0088] The original optimization problem is equivalent to designing signals such that The maximum. Since the second part is a constant, it doesn't need to be considered; and in the first part of the integration, if the integrand can be maximized, then the overall integral result can also be maximized. Therefore, taking the logarithm of the integrand... The first and second derivatives can be expressed as:

[0089]

[0090] Since the second derivative is always less than zero, the Lagrange function reaches its maximum value at the zero point of the first derivative. Setting the first derivative to zero, we obtain the expression for the transmitted signal ESD:

[0091]

[0092] Considering that the left side of the equation is always not less than zero, the expression is changed to:

[0093]

[0094] The value of is determined by E (energy constraint value), and a suitable value can be obtained through interval search. Values. It should be noted that when... When it is impossible to find a zero point for the first derivative, choosing 0 as a substitute is determined by the monotonicity of the first derivative. In this case, choosing 0 can guarantee the maximum result.

[0095] S25. Obtain the optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximized.

[0096] Time-domain constant-modulus signal design: Assume the amplitude of the transmitted signal is A, and its phase sequence is... , where N is the length of the discrete signal sequence. Then the discrete signal can be:

[0097]

[0098] Its discrete Fourier transform can be expressed as:

[0099]

[0100] The square obtainable energy spectrum is:

[0101]

[0102] The ESD to be optimized approximates the optimal ESD (the result of the water-filling method) in the least square sense as the optimization criterion:

[0103]

[0104] The water-filling method is an optimization algorithm, and its core idea is to distribute the energy of the transmitted waveform to the frequency bands with lower clutter, so that the signals in these frequency bands can be more effectively reflected by the target and received. By optimizing the energy distribution in the frequency domain through the water-filling method, the clutter interference can be effectively suppressed, and the signal-to-clutter ratio can be improved.

[0105] S26, based on the preset constant modulus constraint condition, the arbitrary signal waveform is projected into the signal set with the same frequency domain characteristics as the optimal energy spectrum density and the constant modulus signal set through the alternating projection algorithm for iteration.

[0106] S27, based on the preset number of iterations, a target constant modulus signal waveform is obtained, in which the similarity between the frequency domain energy spectrum density and the optimal energy spectrum density is greater than a threshold value.

[0107] The amplitude of the transmitted signal is set to a constant value A, and the phase sequence is randomly generated. The alternating projection algorithm is used to project the time-domain generated constant modulus signal into the signal set with the same frequency domain characteristics as the optimal ESD, to obtain the projected signal. The projected signal is transformed into the time domain, the phase is kept unchanged, and the amplitude is modified to A, to complete one iteration process. The above iteration process is repeated until the frequency domain characteristics of the obtained constant modulus signal are consistent with the expected ESD.

[0108] Specifically, first, a signal set is selected, which contains all the signals with the same ESD as in the interval [-B / 2, B / 2]. When designing the signal, a constant modulus signal s(t) is first generated in the time domain, with a random phase and an amplitude of A and a duration of T. After transforming the signal into the frequency domain, its expression is:

[0109]

[0110] The signal is projected into the signal set In this way, the result of the projection is the signal in the set that is closest to the signal s(t). It is not difficult to see that the result of the projection is the signal in the set whose phase is the same as the phase of the original signal in the frequency domain, and its frequency domain expression is:

[0111]

[0112] After obtaining this projection signal, its inverse Fourier transform is calculated to the time domain, and the time domain signal is obtained:

[0113]

[0114] Keeping the phase unchanged and modifying its amplitude to A, at this time the projection of the frequency domain signal to the constant envelope set is completed. The set includes all signals whose amplitude is constant A within the time duration [-T / 2, T / 2]. The final time domain signal expression is:

[0115]

[0116] The above completes one iteration process of the alternating projection method. The obtained constant modulus signal is used as the input of the next iteration, and the cycle is repeated to obtain the constant modulus signal whose ESD is close to the expected ESD, and the ESD and the expected ESD are compared as shown in Figure 5 .

[0117] It can be seen that the frequency domain characteristics of the designed constant modulus signal are consistent with the expected ESD. Figure 6 is the echo signal obtained by using the linear frequency modulation signal for target detection, Figure 7 is the echo signal obtained by using the optimized transmit waveform in Figure 5 . By comparing the peak values of the clutter and target signals in the two figures, it can be seen that the optimized transmit signal can effectively suppress the clutter and maximize the output signal-to-clutter ratio, thereby improving the target detection efficiency.

[0118] S28, detecting the target again by transmitting the target constant modulus signal waveform by the cognitive radar.

[0119] S29, obtaining the feedback signal echo obtained after transmitting the target constant modulus signal waveform, and performing the step of calculating the signal-to-clutter ratio of the output signal after the matched filter based on the feedback signal echo.

[0120] Finally, the target is detected again by transmitting the target constant modulus signal waveform by the cognitive radar; and the step of maximizing the signal-to-clutter ratio of the cognitive radar constant modulus waveform design is continued by obtaining the feedback signal echo obtained after transmitting the target constant modulus signal waveform.

[0121] The embodiment of the present application adjusts the radar waveform through the interaction of radar and environment, which is different from the frequency domain energy constraint in the traditional waveform design, and does not constrain the time domain waveform synthesis, the method introduces not only the energy constraint in the frequency domain, but also the constant modulus constraint in the time domain signal synthesis stage, and realizes the synthesis of the time domain waveform by using the alternating projection algorithm. The amplitude of the transmitted waveform is ensured to be constant, which helps to reduce the nonlinear distortion of the amplifier and improve the detection accuracy.

[0122] The embodiment of the present application optimizes the energy distribution in the frequency domain by the water injection method, can concentrate the signal energy to the frequency band with less clutter, thereby effectively suppressing the clutter interference and improving the SCNR. The constant envelope constraint in the time domain signal synthesis is considered: the constant envelope constraint of the time domain waveform is ensured by the alternating projection algorithm, which is very important for the actual hardware design of the radar system, because most radar transmission systems require constant envelope signals to maintain stable transmission power. The Durbin method does not have the specific design constraint of time domain constant envelope, which may cause power fluctuation, and the accuracy of the stationary phase method depends on the signal frequency, and in the case of low frequency or slow phase change, the accuracy of the method will decrease significantly. If the frequency of the signal is low, or the phase change is not enough, the stationary phase method may not provide effective approximation.

[0123] Iterative optimization process: the embodiment of the present application can gradually reduce the error between the designed waveform and the target waveform in the frequency domain and the time domain through the iterative optimization of alternating projection, and finally achieve more accurate waveform design effect. The stationary phase method and the Durbin method do not have similar iterative optimization process, and may not achieve the optimization effect of the method in some complex scenarios.

[0124] Overall, the embodiment of the present application not only has better adaptability in complex clutter environment, but also significantly improves the target detection performance by combining constant envelope and frequency domain optimization while balancing the time domain and frequency domain characteristics.

[0125] The device for designing the constant modulus waveform of the cognitive radar based on the maximum signal-to-clutter ratio provided by the present application is described below, and the device for designing the constant modulus waveform of the cognitive radar based on the maximum signal-to-clutter ratio described below can be correspondingly referred to the method for designing the constant modulus waveform of the cognitive radar based on the maximum signal-to-clutter ratio described above.

[0126] Figure 8 It is a structure schematic diagram of the device for designing the constant modulus waveform of the cognitive radar based on the maximum signal-to-clutter ratio provided by the present application, and specifically includes:

[0127] The acquisition module 801 is configured to acquire a feedback signal echo obtained after a cognitive radar transmitting signal, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component is an output after the transmitting signal is convolved with a unit impulse response of a target, and the clutter echo component is an output after the transmitting signal is reflected by a clutter scattering point. The target echo component is the clutter echo component. For details, refer to the related description of the method embodiment.

[0128] The design module 802 is configured to calculate a signal-to-clutter-and-noise ratio of an output signal after a matched filter based on the feedback signal echo. For details, refer to the related description of the method embodiment.

[0129] The design module 802 is further configured to acquire an optimal energy spectral density of the transmitting signal when the signal-to-clutter-and-noise ratio is maximum under a preset energy constraint condition. For details, refer to the related description of the method embodiment.

[0130] The determination module 803 is configured to determine a target constant modulus signal waveform based on the optimal energy spectral density. For details, refer to the related description of the method embodiment.

[0131] Figure 9 An example of an entity structure diagram of an electronic device is shown in FIG. 8. Figure 9 As shown in FIG. 8, the electronic device can include a processor 810, a communications interface 820, a memory 830, and a communications bus 840, wherein the processor 810, the communications interface 820, and the memory 830 complete mutual communication through the communications bus 840. The processor 810 can invoke a logic instruction in the memory 830 to execute a cognitive radar constant modulus waveform design method based on maximum signal-to-clutter-and-noise ratio, which includes: acquiring a feedback signal echo obtained after a cognitive radar transmitting signal, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component is an output after the transmitting signal is convolved with a unit impulse response of a target, and the clutter echo component is an output after the transmitting signal is reflected by a clutter scattering point; calculating a signal-to-clutter-and-noise ratio of an output signal after a matched filter based on the feedback signal echo; acquiring an optimal energy spectral density of the transmitting signal when the signal-to-clutter-and-noise ratio is maximum under a preset energy constraint condition; and determining a target constant modulus signal waveform based on the optimal energy spectral density.

[0132] Further, the logic instructions in the memory 830 described above can be implemented by a software functional unit and sold or used as an independent product, which can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or partially contribute to the prior art, or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0133] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to execute the maximum signal-to-clutter-and-noise ratio based cognitive radar constant modulus waveform design method provided by the above-mentioned methods. The method comprises: obtaining a feedback signal echo obtained after a cognitive radar transmit signal, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component is the output after the transmit signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmit signal is reflected by a clutter scattering point; calculating the signal-to-clutter-and-noise ratio of the output signal after a matched filter based on the feedback signal echo; obtaining the optimal energy spectral density of the transmit signal when the signal-to-clutter-and-noise ratio is maximum under a preset energy constraint condition; and determining a target constant modulus signal waveform based on the optimal energy spectral density.

[0134] In another aspect, the present application also provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the maximum signal-to-clutter-and-noise ratio based cognitive radar constant modulus waveform design method provided by the above-mentioned methods. The method comprises: obtaining a feedback signal echo obtained after a cognitive radar transmit signal, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component is the output after the transmit signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmit signal is reflected by a clutter scattering point; calculating the signal-to-clutter-and-noise ratio of the output signal after a matched filter based on the feedback signal echo; obtaining the optimal energy spectral density of the transmit signal when the signal-to-clutter-and-noise ratio is maximum under a preset energy constraint condition; and determining a target constant modulus signal waveform based on the optimal energy spectral density.

[0135] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0136] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and the necessary general hardware platform, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0137] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for designing constant-mode waveforms for cognitive radar based on maximizing the signal-to-clutter-to-noise ratio, characterized in that, include: The feedback signal echo obtained after the cognitive radar transmits a signal includes a target echo component and a clutter echo component. The target echo component is the output after the unit impulse response of the transmitted signal and the target is convolved, and the clutter echo component is the output after the transmitted signal is reflected by the clutter scattering point. The signal-to-noise ratio (SNR) of the output signal after passing through the matched filter is calculated based on the feedback signal echo. Under a preset energy constraint, obtain the optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximized; The target constant-mode signal waveform is determined based on the optimal energy spectral density; The determination of the target constant-mode signal waveform based on the optimal energy spectral density includes: Based on the preset constant modulus constraint, an arbitrary signal waveform is projected onto a set of signals and a set of constant modulus signals with the same frequency domain characteristics as the optimal energy spectral density through an alternating projection algorithm for iteration. Based on a preset number of iterations, a target constant-mode signal waveform is obtained in which the similarity between the frequency domain energy spectral density and the optimal energy spectral density is greater than a threshold.

2. The method according to claim 1, characterized in that, The calculation of the signal-to-noise ratio (SNR) of the output signal after the matched filter based on the feedback signal echo includes: The feedback signal echo is input into a preset signal transmission system model, and the signal-to-noise ratio of the output signal is calculated through the linear convolution operation of the filter.

3. The method according to claim 2, characterized in that, The step of obtaining the optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximized under a preset energy constraint includes: The energy spectral density of the transmitted signal is designed using the Lagrange multiplier method. Under a preset energy constraint, the signal-to-clutter-to-noise ratio (SCR) of the transmitted signal at any given time is optimized with the goal of maximizing the SCR. Obtain the optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximized.

4. The method according to claim 1, characterized in that, The step of iteratively projecting arbitrary signal waveforms onto a set of signals and a set of constant-mode signals with the same frequency domain characteristics as the optimal energy spectral density, based on a preset constant-mode constraint, using an alternating projection algorithm, includes: Based on the preset constant modulus constraint, a set of signal waveforms is selected and the error in energy spectral density between any signal waveform in the set and the target waveform is gradually reduced through an alternating projection algorithm.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: The target is detected again by transmitting the target constant modulus signal waveform through the cognitive radar; After obtaining the feedback signal echo obtained after transmitting the target constant mode signal waveform, the step of calculating the signal-to-noise ratio of the output signal after passing through the matched filter based on the feedback signal echo is performed.

6. A cognitive radar constant-mode waveform design device based on maximizing signal-to-clutter-to-noise ratio, characterized in that, include: The acquisition module is used to acquire the feedback signal echo obtained after the cognitive radar transmits a signal. The feedback signal echo includes a target echo component and a clutter echo component. The target echo component is the output after the unit impulse response of the transmitted signal and the target is convolved. The clutter echo component is the output after the transmitted signal is reflected by the clutter scattering point. The design module is used to calculate the signal-to-noise ratio (SNR) of the output signal after passing through the matched filter based on the feedback signal echo. The design module is also used to obtain the optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximized under preset energy constraints. The determination module is used to determine the target constant-mode signal waveform based on the optimal energy spectral density; the determination of the target constant-mode signal waveform based on the optimal energy spectral density includes: based on preset constant-mode constraints, iterating by projecting any signal waveform onto a set of signals and a set of constant-mode signals with the same frequency domain characteristics as the optimal energy spectral density using an alternating projection algorithm; and obtaining the target constant-mode signal waveform whose frequency domain energy spectral density is more similar to the optimal energy spectral density than a threshold based on a preset number of iterations.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the cognitive radar constant mode waveform design method based on maximizing the signal-to-clutter-to-noise ratio as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the cognitive radar constant mode waveform design method based on maximizing the signal-to-clutter-to-noise ratio as described in any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the cognitive radar constant mode waveform design method based on maximizing the signal-to-clutter-to-noise ratio as described in any one of claims 1 to 5.

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