Cognitive radar constant modulus waveform design method and device based on maximum signal-clutter-noise ratio

Abstract

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

Description

Technical Field

[0001] The present invention relates to the technical field of cognitive radar and radar waveform design, and in particular to a cognitive radar constant modulus waveform design method and device based on maximizing signal-to-noise ratio. Background Art

[0002] Traditional radars usually transmit fixed waveforms (such as linear frequency modulation waveforms, pulse waveforms, etc.). However, these waveforms have limitations in dynamic and complex electromagnetic environments (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 concept is to enable the radar system to perceive 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 complex environments. 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. At this time, the environmental information is the background clutter signal. By substituting it into the expression of SCNR, the frequency domain response of the optimal waveform can be solved, and then the time domain transmission waveform can be synthesized. In the frequency domain response design stage, the water injection method is generally used to distribute the waveform energy to reduce the impact of clutter on target detection; in the time domain waveform synthesis stage, the more widely used methods are iterative algorithms such as the Durbin method and the interior point method.

[0004] In the process of waveform design to maximize the signal-to-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: The Durbin method is a method for synthesizing time domain signals, which is usually used in the moving average (MA) model spectrum estimation. Its characteristic is that the synthesized signal is a minimum phase signal. First, by performing an inverse Fourier transform on the expected ESD, the autocorrelation function of the target time domain signal can be obtained. The Levinson algorithm can be used to find the optimal linear prediction coefficient. At the same time, the autocorrelation function is substituted into the Yule Walker equation, and the MA coefficient is solved to obtain the time domain waveform to be designed. This method does not consider the modulus length of the time domain signal, and cannot achieve the design goal under constraints such as constant modulus and peak-to-average power ratio.

[0005] Another method is to synthesize time domain signals based on the stationary phase principle. The core idea is that in an integral, when the phase changes dramatically, only the region with a slower phase change contributes significantly to the integral. Specifically, the stationary phase method finds stationary points in the integral (i.e. points where the phase derivative is zero). The contribution near these points is much greater than that of other regions, so the integral value can be approximately calculated. By calculating the known energy spectrum signal, the group delay function of the signal can be obtained. , the frequency modulation function of the signal can be obtained by finding the inverse function of the group delay, and then the phase of the signal can be obtained. Although the time domain modulus of the transmitted signal can be controlled, the effectiveness of the stationary phase method depends on the rapid change of the phase function. Therefore, the accuracy of this method will be significantly reduced at low frequencies or when the phase changes slowly. If the frequency of the signal is low or the phase change is not drastic enough, the stationary phase method may not provide an effective approximation.

[0006] In practical applications, the synthesized time domain signal often needs to meet the constant modulus constraint, which is to ensure that the nonlinear power amplifier remains in the efficient working range and reduce nonlinear distortion, thereby improving the energy utilization of the system. At the same time, during the transmission of the constant modulus signal, the waveform energy is evenly distributed, which reduces the dependence on signal amplitude modulation, enhances the anti-interference performance of the radar signal in complex environments, and is conducive to target detection. Existing technologies still face great challenges in accurately synthesizing the optimal waveform that meets the dual constraints of the time domain and frequency domain, especially in achieving constant envelope and optimizing ESD consistency. Summary of the invention

[0007] The present invention provides a cognitive radar constant modulus waveform design method and device based on maximizing the signal-to-noise ratio, which is used to solve the defects of cognitive radar in the prior art that has limitations in complex environments and cannot be adaptively adjusted according to real-time environmental changes, so as to achieve better adaptability in complex clutter environments, maintain a balance between time domain and frequency domain characteristics, and improve target detection performance.

[0008] The present invention provides a cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio, comprising: Acquire a feedback signal echo obtained after the cognitive radar transmits a signal, wherein the feedback signal echo includes a target echo component and a clutter echo component, the target echo component is the output after the transmit signal is convolved with a 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; Calculate the signal-to-noise ratio of the output signal after passing through the matched filter based on the feedback signal echo; Under a preset energy constraint condition, obtaining an optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximum; A target constant modulus signal waveform is determined based on the optimal energy spectral density.

[0009] In a possible implementation, the method further 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 a linear convolution operation of a filter.

[0010] In a possible implementation, the method further includes: The energy spectrum density of the transmission signal is designed by using Lagrange multiplier method; Under a preset energy constraint, optimizing the signal-to-noise ratio of the transmitted signal at any time with the goal of maximizing the signal-to-noise ratio; The optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximum is obtained.

[0011] In a possible implementation, the method further includes: Based on a preset constant modulus constraint condition, an arbitrary signal waveform is projected onto a signal set and a constant modulus signal set having the same frequency domain characteristics as the optimal energy spectral density by an alternating projection algorithm for iteration; Based on a preset number of iterations, a target constant modulus signal waveform is obtained, the similarity between the frequency domain energy spectrum density and the optimal energy spectrum density being greater than a threshold.

[0012] In a possible implementation, the method further includes: Based on the preset constant modulus constraint condition, a signal waveform set is selected and an alternating projection algorithm is used to gradually reduce the error in energy spectral density between any signal waveform in the signal waveform set and the target waveform.

[0013] In a possible implementation, the method further includes: emitting the target constant modulus signal waveform by the cognitive radar to detect the target again; Acquire a feedback signal echo obtained after transmitting the target constant modulus signal waveform, and perform 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.

[0014] The present invention also provides a cognitive radar constant modulus waveform design device based on maximizing the signal-to-noise ratio, comprising the following modules: An acquisition module is used to acquire a feedback signal echo obtained after the cognitive radar transmits a signal, wherein the feedback signal echo includes a target echo component and a clutter echo component, the target echo component is the output after the transmission signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by the clutter scattering point; A design module, used for calculating the signal-to-noise ratio of the output signal after passing through the matched filter based on the feedback signal echo; The design module is further used to obtain the optimal energy spectrum density of the transmitted signal when the signal-to-noise ratio is maximum under a preset energy constraint condition; A determination module is used to determine a target constant modulus signal waveform based on the optimal energy spectrum density.

[0015] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for designing a constant modulus waveform of a cognitive radar based on maximizing the signal-to-noise ratio as described above is implemented.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for designing a constant modulus waveform of a cognitive radar based on maximizing the signal-to-noise ratio as described above is implemented.

[0017] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for designing a constant modulus waveform of a cognitive radar based on maximizing the signal-to-noise ratio as described above is implemented.

[0018] The present invention provides a cognitive radar constant modulus waveform design method and device based on maximizing the signal-to-noise ratio. The method and device are as follows: a feedback signal echo is obtained after the cognitive radar transmits a signal, wherein the feedback signal echo includes 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; the signal-to-noise ratio of the output signal after passing through a matched filter is calculated based on the feedback signal echo; under a preset energy constraint, the optimal energy spectral density of the transmit signal when the signal-to-noise ratio is maximum is obtained; and the target constant modulus signal waveform is determined based on the optimal energy spectral density. Compared with the existing technology, cognitive radar has limitations in complex environments and cannot be adaptively adjusted according to real-time environmental changes. This solution dynamically adjusts the radar waveform through the interaction between the radar and the environment. In the time domain signal synthesis stage, not only the energy constraint in the frequency domain is considered, but also the constant modulus constraint is introduced. The time domain waveform is synthesized using the alternating projection algorithm, which ensures the constant amplitude of the transmitted waveform, helps reduce the nonlinear distortion of the amplifier, has better adaptability in complex clutter environments, maintains a balance between time domain and frequency domain characteristics, and improves target detection performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is one of the flow charts of the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio provided by the present invention.

[0021] Figure 2 This is the second flow chart of the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio provided by the present invention.

[0022] Figure 3 This is the third flow chart of the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio provided by the present invention.

[0023] Figure 4 It is a schematic diagram of the signal transmission system model provided by the present invention.

[0024] Figure 5 It is a schematic diagram comparing the energy spectrum density of the target constant modulus signal waveform provided by the present invention and the expected energy spectrum density.

[0025] Figure 6 It is a schematic diagram of a feedback signal echo corresponding to the transmission signal provided by the present invention.

[0026] Figure 7 It is a schematic diagram of a feedback signal echo corresponding to the optimized target constant modulus signal waveform provided by the present invention.

[0027] Figure 8 It is a structural schematic diagram of a cognitive radar constant modulus waveform design device based on maximizing the signal-to-noise ratio provided by the present invention.

[0028] Fig. 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] To facilitate understanding of the embodiments of the present invention, specific embodiments will be further explained below in conjunction with the accompanying drawings. The embodiments do not constitute a limitation on the embodiments of the present invention.

[0031] Figure 1 This is one of the flow charts of the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio provided by the present invention, such as Figure 1 As shown, the method specifically includes: S11. Acquire a feedback signal echo obtained after the cognitive radar transmits a signal.

[0032] The embodiment of the present invention proposes a two-step waveform design method, aiming to achieve constant modulus waveform design that maximizes the signal-to-noise ratio. The method includes an energy spectral density (ESD) design stage and a time domain constant modulus signal design stage, such as Figure 3 shown.

[0033] In an embodiment of the present invention, a constant modulus constraint is introduced in the adaptive radar waveform design to achieve a constant modulus waveform design that maximizes the signal-to-noise ratio. In the optimal ESD design stage, the signal energy is distributed to the frequency band with a small clutter component and a large target component through the water injection method, which can effectively improve the signal-to-clutter-plus-noise ratio (SCNR) during target detection. In the design stage of the time domain signal, it is necessary to solve the constant modulus waveform that meets the optimal ESD conditions. This problem belongs to the phase retrieval problem. The core challenge lies in how to effectively convert between the frequency domain and the time domain while meeting 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, an alternating projection algorithm is introduced to gradually reduce the error between the design waveform and the target waveform in ESD by projecting the design signal onto the template, and finally obtain a waveform that meets the time domain constant envelope constraint and has the smallest frequency domain ESD error.

[0034] Specifically, first, the cognitive radar transmits a target detection signal, and then obtains the feedback signal echo obtained after the transmission signal. The feedback signal echo includes a target echo component and a clutter echo component; the target echo component is the output after the transmission signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by the clutter scattering point.

[0035] S12: Calculate the signal-to-noise ratio of the output signal after passing through the matched filter based on the feedback signal echo.

[0036] The embodiment of the present invention pre-establishes a signal transmission system model in a single-transmit and single-receive system, and regards the target echo component and the clutter echo component in the feedback signal echo as the output of the transmission signal after passing through the linear system. The signal-to-noise ratio of the transmission signal at any time is calculated through the linear convolution operation of the filter in the signal transmission system model.

[0037] S13. Under a preset energy constraint condition, obtain an optimal energy spectrum density of the transmission signal when the signal-to-noise ratio is maximum.

[0038] Then, the energy-limited energy spectral density design is performed: the signal energy spectral density is designed using the Lagrange multiplier method, and the energy spectral density expression of the transmitted signal is determined by solving the maximum value of the Lagrangian function. Then, under the preset energy constraint, the signal-to-noise ratio at any time of the transmitted signal is optimized with the goal of maximizing the signal-to-noise ratio; the optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximized is obtained.

[0039] S14. Determine a target constant modulus signal waveform based on the optimal energy spectrum density.

[0040] Finally, the time domain constant modulus signal is designed: the amplitude of the transmitted signal is set to a constant value A, and its phase sequence is randomly generated. Using the alternating projection algorithm, the constant modulus signal generated in the time domain is projected onto a signal set with the same frequency domain characteristics as the optimal energy spectral density to obtain a projection signal. The projection signal is transformed into the time domain, the phase is kept unchanged, and its amplitude is modified to A to complete an iterative process. Repeat the iterative process until the obtained frequency domain characteristics of the constant modulus signal match the desired energy spectral density, and the target constant modulus signal waveform is obtained.

[0041] The target is detected again by transmitting the target constant modulus signal waveform through the cognitive radar; the feedback signal echo obtained after obtaining the transmitted target constant modulus signal waveform continues to perform the cognitive radar constant modulus waveform design steps to maximize the signal-to-noise ratio.

[0042] The embodiment of the present invention dynamically adjusts the radar waveform through the interaction between the radar and the environment. Different from the frequency domain energy constraint in the traditional waveform design, 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. It ensures the constant amplitude of the transmitted waveform, helps to reduce the nonlinear distortion of the amplifier, and improves the detection accuracy.

[0043] The present invention provides a cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio. The method comprises the following steps: obtaining a feedback signal echo after the cognitive radar transmits a signal, wherein the feedback signal echo includes a target echo component and a clutter echo component, the target echo component is the output after the transmission signal is convolved with a unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by a clutter scattering point; calculating the signal-to-noise ratio of the output signal after passing through a matched filter based on the feedback signal echo; obtaining the optimal energy spectral density of the transmission signal when the signal-to-noise ratio is maximum under a preset energy constraint; and determining the target constant modulus signal waveform based on the optimal energy spectral density. Compared with the existing technology, cognitive radar has limitations in complex environments and cannot be adaptively adjusted according to real-time environmental changes. This method dynamically adjusts the radar waveform through the interaction between the radar and the environment. In the time domain signal synthesis stage, not only the energy constraint in the frequency domain is considered, but also the constant modulus constraint is introduced. The time domain waveform is synthesized using the alternating projection algorithm, which ensures that the amplitude of the transmitted waveform is constant, helps to reduce the nonlinear distortion of the amplifier, has better adaptability in complex clutter environments, maintains a balance between time domain and frequency domain characteristics, and improves target detection performance.

[0044] Figure 2 FIG. 2 is a flow chart of the method for designing a constant modulus waveform of a cognitive radar based on maximizing the signal-to-noise ratio provided by the present invention. Figure 2 As shown, the method specifically includes: S21. Acquire a feedback signal echo obtained after the cognitive radar transmits a signal.

[0045] The embodiment of the present invention proposes a two-step waveform design method, aiming to achieve constant modulus waveform design that maximizes the signal-to-noise ratio. The method includes an energy spectral density (ESD) design stage and a time domain constant modulus signal design stage, such as Figure 3 shown.

[0046] In an embodiment of the present invention, a constant modulus constraint is introduced in the adaptive radar waveform design to achieve a constant modulus waveform design that maximizes the signal-to-noise ratio. In the optimal ESD design stage, the signal energy is distributed to the frequency band with a small clutter component and a large target component through the water injection method, which can effectively improve the signal-to-clutter-plus-noise ratio (SCNR) during target detection. In the design stage of the time domain signal, it is necessary to solve the constant modulus waveform that meets the optimal ESD conditions. This problem belongs to the phase retrieval problem. The core challenge lies in how to effectively convert between the frequency domain and the time domain while meeting 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, an alternating projection algorithm is introduced to gradually reduce the error between the design waveform and the target waveform in ESD by projecting the design signal onto the template, and finally obtain a waveform that meets the time domain constant envelope constraint and has the smallest frequency domain ESD error.

[0047] Specifically, first, the cognitive radar transmits a target detection signal, and then obtains the feedback signal echo obtained after the transmission signal. The feedback signal echo includes a target echo component and a clutter echo component; the target echo component is the output after the transmission signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by the clutter scattering point.

[0048] S22: input the feedback signal echo into a preset signal transmission system model, and calculate the signal-to-noise ratio of the output signal through a linear convolution operation of a filter.

[0049] The embodiment of the present invention pre-establishes a signal transmission system model in a single-transmit and single-receive system. Figure 4 As shown in FIG. 1 , the target echo component and the clutter echo component in the feedback signal echo are regarded as the output of the transmitted signal after passing through the linear system and respectively. The signal-to-noise ratio of the output signal is calculated through the linear convolution operation of the filter in the signal transmission system model.

[0050] Specifically, the waveform of a transmitted signal is: , the target echo component and clutter echo component in the echo are regarded as the transmitting signal Through the linear system and The output after is the unit impulse response of the target and the clutter respectively. At the receiving end, the echo and the additive noise enter the filter together. , the output is .

[0051] Assume the filter input signal is , then: Among them, * represents the linear convolution operation, It can be expressed as the superposition of several impulse signals with different time delays, each impulse signal represents a target reflection point on a distance unit (the embodiment of the present invention adopts a point target, i.e. ), is noise. The signal after the filter is: At this moment, the SCNR of the output signal can be expressed as: Converted to frequency domain: in are the energy spectral densities of clutter and noise respectively, and the others are the Fourier transforms (FT) of the corresponding responses. . According to the Cauchy-Schwarz inequality, SCNR can be scaled to: It can be seen that when the filter satisfies: When , the equality is established. Considering the actual radar system, the frequency range of the transmitted signal is , where B is the transmission signal bandwidth, the signal is a constant modulus signal, and the time domain amplitude is A. Then the final optimization problem can be transformed into: S23, using Lagrange multiplier method to design the energy spectrum density of the transmission signal.

[0052] S24. Under a preset energy constraint, optimizing the signal-to-noise ratio of the transmitted signal at any time with the goal of maximizing the signal-to-noise ratio.

[0053] Energy-limited energy spectral density (ESD) design: Use the Lagrange multiplier method to design the signal energy spectral density, and determine the ESD expression of the transmitted signal by solving the maximum value of the Lagrangian function. Then, under the preset energy constraint, the signal-to-noise ratio is optimized with the goal of maximizing the signal-to-noise ratio.

[0054] Specifically, for energy constraints, the Lagrange multiplier method can be used to design the signal energy spectrum density. Assume that the Lagrange multiplier is , then the Lagrangian function can be written as: The original optimization problem is equivalent to designing the signal so that The second part is a constant, so it does not need to be considered; and in the first part of the integral, if the integrand can be maximized, the total integral result can also be maximized. Then find the integrand The first and second order derivatives of can be expressed as: Since the second-order derivative is always less than zero, the Lagrangian function can reach its maximum value at the zero point of the first-order derivative. Let the first-order derivative be 0, and the ESD expression of the transmitted signal can be obtained: Considering that the left side of the equation is always not less than zero, the expression is changed to: The value of is determined by E (energy constraint value), and a suitable It should be noted that when When it is impossible to find the zero point of the first-order derivative, choosing 0 as a substitute is determined by the monotonicity of the first-order derivative. At this time, taking 0 can ensure the maximum result.

[0055] S25. Obtain an optimal energy spectral density of the transmission signal when the signal-to-noise ratio is maximum.

[0056] Time domain constant modulus signal design: Assume that 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: Its discrete Fourier transform can be expressed as: The energy spectrum can be obtained by squaring: The optimization criterion is that the ESD to be optimized approaches the optimal ESD (result of water injection method) in the sense of minimum mean square: The water injection method is an optimization algorithm whose 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 and received by the target. By optimizing the energy distribution in the frequency domain, the water injection method can effectively suppress clutter interference and improve the signal-to-noise ratio.

[0057] S26. Based on a preset constant modulus constraint condition, an arbitrary signal waveform is projected onto a signal set and a constant modulus signal set having the same frequency domain characteristics as the optimal energy spectral density by an alternating projection algorithm for iteration.

[0058] S27. Based on a preset number of iterations, a target constant modulus signal waveform is obtained, wherein the similarity between the frequency domain energy spectrum density and the optimal energy spectrum density is greater than a threshold.

[0059] The amplitude of the transmitted signal is set to a constant value A, and its phase sequence is randomly generated. Using the alternating projection algorithm, the constant modulus signal generated in the time domain is projected onto a signal set with the same frequency domain characteristics as the optimal ESD to obtain a projection signal. The projection signal is transformed into the time domain, the phase is kept unchanged, and its amplitude is modified to A to complete an iterative process. Repeat the above iterative process until the obtained constant modulus signal frequency domain characteristics match the desired ESD.

[0060] Specifically, first select a signal set , this set includes all ESDs in the interval [-B / 2, B / 2] and The same signal. When designing the signal, first generate a constant modulus signal s(t) in the time domain, whose phase is randomly generated, amplitude is A, and duration is T. After the signal is transformed into the frequency domain, its expression is: Project the signal to the signal collection In the above example, the projection result is the signal in the set that is closest to the signal s(t). It is not difficult to see that the projection result is the set The frequency domain expression of the signal with the same phase as the original signal is: After obtaining this projection signal, we need to perform inverse Fourier transform to the time domain, and obtain its time domain signal as follows: Keep the phase unchanged and change its amplitude to A. At this time, the frequency domain signal is converted to a constant envelope set. The projection of . This set includes all signals with a constant amplitude of A within the duration [-T / 2, T / 2]. The final time domain signal expression is: The above completes one iteration of the alternating projection method. The constant modulus signal obtained is used as the input of the next iteration. By repeating the process in sequence, a constant modulus signal with an ESD close to the expected ESD can be obtained. The comparison between its ESD and the expected ESD is as follows: Figure 5 shown.

[0061] It can be seen that the designed constant mode signal frequency domain characteristics are consistent with the expected ESD. Figure 6 is the echo signal for target detection using a linear frequency modulation signal. Figure 7 is used Figure 5The echo signal obtained by the optimized transmission waveform in . Comparing the peak values ​​of the clutter and target signals in the two figures, it can be seen that the optimized transmission signal can effectively suppress clutter and maximize the output signal-to-noise ratio, thereby improving the target detection efficiency.

[0062] S28. Detect the target again by emitting the target constant modulus signal waveform through the cognitive radar.

[0063] S29, acquiring a feedback signal echo obtained after transmitting the target constant modulus signal waveform, and executing 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.

[0064] Finally, the target is detected again by transmitting the target constant modulus signal waveform through the cognitive radar; the feedback signal echo obtained after the target constant modulus signal waveform is transmitted continues to carry out the cognitive radar constant modulus waveform design step to maximize the signal-to-noise ratio.

[0065] The embodiment of the present invention dynamically adjusts the radar waveform through the interaction between the radar and the environment. Different from the frequency domain energy constraint in the traditional waveform design, 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. It ensures the constant amplitude of the transmitted waveform, helps to reduce the nonlinear distortion of the amplifier, and improves the detection accuracy.

[0066] The embodiment of the present invention optimizes the energy distribution in the frequency domain through the water injection method, and can concentrate the signal energy on the frequency band with less clutter, thereby effectively suppressing clutter interference and improving SCNR. At the same time, the constant envelope constraint during 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 a constant envelope signal to maintain a stable transmission power. However, the Durbin method does not have the specific design constraint of a constant envelope in the time domain, which may cause power fluctuations. The accuracy of the stationary phase method depends on the signal frequency. In the case of low frequency or slow phase changes, the accuracy of this method will be significantly reduced. If the frequency of the signal is low, or the phase change is not drastic enough, the stationary phase method may not provide an effective approximation.

[0067] Iterative optimization process: The embodiment of the present invention can gradually reduce the error between the design waveform and the target waveform in the frequency domain and time domain through iterative optimization of alternating projections, and finally achieve a more accurate waveform design effect. However, the stationary phase method and Durbin method do not have similar iterative optimization processes, and may not achieve the optimization effect of the method in this paper in some complex scenarios.

[0068] In general, the embodiments of the present invention not only have better adaptability in complex clutter environments, but also significantly improve the target detection performance while maintaining the balance between time domain and frequency domain characteristics through the combination of constant envelope and frequency domain optimization.

[0069] The following is a description of a cognitive radar constant modulus waveform design device based on maximizing the signal-to-noise ratio provided by the present invention. The cognitive radar constant modulus waveform design device based on maximizing the signal-to-noise ratio described below and the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio described above can refer to each other.

[0070] Figure 8 : is a schematic diagram of the structure of a cognitive radar constant modulus waveform design device based on maximizing the signal-to-noise ratio provided by the present invention, which specifically includes: The acquisition module 801 is used to acquire the feedback signal echo obtained after the cognitive radar transmits the signal, wherein the feedback signal echo includes a target echo component and a clutter echo component, wherein the target echo component is the output after the transmission signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by the clutter scattering point. Target echo component clutter echo component. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0071] The design module 802 is used to calculate the signal-to-noise ratio of the output signal after passing through the matched filter based on the feedback signal echo. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0072] The design module 802 is further configured to obtain the optimal energy spectrum density of the transmitted signal when the signal-to-noise ratio is maximum under a preset energy constraint condition. Detailed descriptions refer to the relevant descriptions corresponding to the above method embodiments, which will not be repeated here.

[0073] The determination module 803 is used to determine the target constant modulus signal waveform based on the optimal energy spectrum density. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0074] Fig. 9 An example of a physical structure diagram of an electronic device is shown in FIG. Fig. 9As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820 and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio, the method comprising: obtaining a feedback signal echo obtained after the cognitive radar transmits a 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 transmission signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by the clutter scattering point; based on the feedback signal echo, the signal-to-noise ratio of the output signal after the matched filter is calculated; under a preset energy constraint, the optimal energy spectrum density of the transmission signal when the signal-to-noise ratio is maximized is obtained; and the target constant modulus signal waveform is determined based on the optimal energy spectrum density.

[0075] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0076] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio provided by the above methods. The method includes: obtaining a feedback signal echo obtained after the cognitive radar transmits a signal, wherein the feedback signal echo includes a target echo component and a clutter echo component, the target echo component is the output after the transmission signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by a clutter scattering point; based on the feedback signal echo, calculating the signal-to-noise ratio of the output signal after passing through the matched filter; under a preset energy constraint, obtaining the optimal energy spectral density of the transmission signal when the signal-to-noise ratio is maximum; and determining the target constant modulus signal waveform based on the optimal energy spectral density.

[0077] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the cognitive radar constant modulus waveform design method based on maximizing the signal-to-noise ratio provided by the above methods, the method comprising: obtaining a feedback signal echo obtained after the cognitive radar transmits a 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 a 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-noise ratio of the output signal after passing through a matched filter based on the feedback signal echo; obtaining the optimal energy spectral density of the transmit signal when the signal-to-noise ratio is maximum under a preset energy constraint; and determining the target constant modulus signal waveform based on the optimal energy spectral density.

[0078] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0079] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cognitive radar constant modulus waveform design method based on maximizing signal-to-noise ratio, characterized in that: include: Acquire a feedback signal echo obtained after the cognitive radar transmits a signal, wherein the feedback signal echo includes a target echo component and a clutter echo component, the target echo component is the output after the transmit signal is convolved with a 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; Calculate the signal-to-noise ratio of the output signal after passing through the matched filter based on the feedback signal echo; Under a preset energy constraint condition, obtaining an optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximum; A target constant modulus signal waveform is determined based on the optimal energy spectral density.

2. The method according to claim 1, characterized in that The calculating, based on the feedback signal echo, the signal-to-noise ratio of the output signal after passing through the matched filter comprises: 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 a linear convolution operation of a filter.

3. The method according to claim 2, characterized in that The step of obtaining the optimal energy spectrum density of the transmitted signal when the signal-to-noise ratio is maximum under the preset energy constraint condition includes: The energy spectrum density of the transmission signal is designed by using Lagrange multiplier method; Under a preset energy constraint, optimizing the signal-to-noise ratio of the transmitted signal at any time with the goal of maximizing the signal-to-noise ratio; The optimal energy spectral density of the transmitted signal when the signal-to-noise ratio is maximum is obtained.

4. The method according to claim 3, characterized in that The step of determining a target constant modulus signal waveform based on the optimal energy spectrum density comprises: Based on a preset constant modulus constraint condition, an arbitrary signal waveform is projected onto a signal set and a constant modulus signal set having the same frequency domain characteristics as the optimal energy spectral density by an alternating projection algorithm for iteration; Based on a preset number of iterations, a target constant modulus signal waveform is obtained, the similarity between the frequency domain energy spectrum density and the optimal energy spectrum density being greater than a threshold.

5. The method according to claim 4, characterized in that The method of iterating by projecting an arbitrary signal waveform onto a signal set and a constant modulus signal set having the same frequency domain characteristics as the optimal energy spectral density based on a preset constant modulus constraint condition through an alternating projection algorithm comprises: Based on the preset constant modulus constraint condition, a signal waveform set is selected and an alternating projection algorithm is used to gradually reduce the error in energy spectral density between any signal waveform in the signal waveform set and the target waveform.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: emitting the target constant modulus signal waveform by the cognitive radar to detect the target again; Acquire a feedback signal echo obtained after transmitting the target constant modulus signal waveform, and perform 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.

7. A cognitive radar constant modulus waveform design device based on maximizing signal-to-noise ratio, characterized in that: include: An acquisition module is used to acquire a feedback signal echo obtained after the cognitive radar transmits a signal, wherein the feedback signal echo includes a target echo component and a clutter echo component, the target echo component is the output after the transmission signal is convolved with the unit impulse response of the target, and the clutter echo component is the output after the transmission signal is reflected by the clutter scattering point; A design module, used for calculating the signal-to-noise ratio of the output signal after passing through the matched filter based on the feedback signal echo; The design module is further used to obtain the optimal energy spectrum density of the transmitted signal when the signal-to-noise ratio is maximum under a preset energy constraint condition; A determination module is used to determine a target constant modulus signal waveform based on the optimal energy spectrum density.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for designing a cognitive radar constant modulus waveform based on maximizing the signal-to-noise ratio as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for designing a cognitive radar constant modulus waveform based on maximizing the signal-to-noise ratio as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for designing a cognitive radar constant modulus waveform based on maximizing the signal-to-noise ratio as described in any one of claims 1 to 6 is implemented.

Images