Self-adaptive environment cognitive radar system based on waveform optimization and optimization method

Abstract

The invention provides a self-adaptive environment cognitive radar system based on waveform optimization and an optimization method, and belongs to the technical field of radar systems.The system comprises a radio frequency module and a baseband signal processing module connected with the radio frequency module, and the baseband signal processing module comprises a processing system unit and a programmable logic unit; the programmable logic unit adopts a waveform optimization algorithm to process the preprocessed digital echo signal so as to dynamically generate an anti-interference waveform digital signal for next signal emission; the waveform optimization algorithm is a closed-loop iterative algorithm based on environmental perception and a signal-clutter-noise ratio maximization criterion; the processing system unit adopts a preset radar signal processing algorithm to process the preprocessed digital echo signal; the programmable logic unit and the processing system unit work cooperatively in parallel to form a first processing link for dynamic waveform optimization and a second processing link for radar signal processing. The method has the advantages of real-time environment cognition, dynamic spectrum optimization and efficient parallel processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar systems, and in particular to a self-adaptive environment cognitive radar system based on waveform optimization and an optimization method. BACKGROUND

[0002] Traditional radar systems usually transmit waveforms with fixed parameters, and extract target information from echoes at the receiving end by using signal processing techniques such as filtering and constant false alarm rate detection. However, in the modern complex electromagnetic environment, fixed transmission waveforms are difficult to cope with dynamic changes in interference and clutter. When the radar waveform continuously transmits energy to the strong clutter frequency band, the signal to clutter plus noise ratio (SCNR) at the receiving end will deteriorate sharply, and the detection performance will decrease. In addition, the signal processing flow of the traditional radar is one-way, that is, transmission, reception and processing. The transmitter cannot adaptively adjust according to the environmental feedback information, and the anti-interference ability completely depends on the receiving end algorithm, which is slow in response and difficult to meet the real-time requirements of modern electronic countermeasures.

[0003] The emergence of cognitive radar technology provides a direction to solve the above problems. Its core idea is to make the system able to perceive the changes of the external electromagnetic environment in real time through the closed-loop interaction between the radar and the environment, and dynamically adjust the transmission waveform parameters, so as to significantly improve the target detection and tracking performance in the interference and clutter environment. However, the existing radar hardware architecture is usually based on industrial computers for centralized processing, which has low computing efficiency and high delay, and is difficult to support real-time waveform optimization calculation required by the closed loop, thereby limiting the practical application of cognitive radar technology. Therefore, a new type of radar system hardware architecture is needed, which can efficiently implement advanced cognitive waveform optimization algorithms at the hardware level to meet the real-time requirements and truly play the technical advantages of cognitive radar. SUMMARY

[0004] The present application provides a self-adaptive environment cognitive radar system based on waveform optimization and an optimization method, which has the advantages of real-time environment cognition, dynamic spectrum optimization and efficient parallel processing.

[0005] In a first aspect, the present application provides a self-adaptive environment cognitive radar system based on waveform optimization, comprising: a radio frequency module and a baseband signal processing module connected to the radio frequency module, the baseband signal processing module comprising a programmable system on a chip integrated with a processing system unit and a programmable logic unit; The programmable logic unit is configured to pre-process the digital echo signal output by the radio frequency module, process the pre-processed digital echo signal by using a waveform optimization algorithm to dynamically generate an anti-interference waveform digital signal, and output the waveform digital signal to the radio frequency module for the next signal transmission. The processing system unit is configured to receive the pre-processed digital echo signal output by the programmable logic unit and process the pre-processed digital echo signal by using a preset radar signal processing algorithm. The programmable logic unit and the processing system unit work in parallel to form a first processing link for dynamic waveform optimization and a second processing link for radar signal processing.

[0006] In some embodiments, the waveform optimization algorithm includes: estimating the environmental interference spectral characteristics based on the pre-processed digital echo signal; iteratively calculating under the constraint of constant modulus of the transmit waveform to maximize the system output signal-to-jamming-and-noise ratio as the optimization target to generate a signal energy spectrum allocation scheme; generating a corresponding time-domain waveform phase encoding sequence according to the signal energy spectrum allocation scheme as the waveform digital signal for the next transmission.

[0007] In some embodiments, the pre-processing includes pulse compression processing.

[0008] In some embodiments, the radio frequency module includes a radio frequency signal processing module, an intermediate frequency signal processing module, and a data conversion module. The waveform digital signal generated by the programmable logic unit is processed by the digital-to-analog converter in the data conversion module, the intermediate frequency transmission channel in the intermediate frequency signal processing module, and the radio frequency transmission channel in the radio frequency module in sequence, and then transmitted by the antenna.

[0009] In some embodiments, the radio frequency signal processing module includes a circulator, a radio frequency transmission channel, a radio frequency receiving channel, and a first local oscillator signal source. The circulator is configured for signal directional transmission and transceiver duplexing between the antenna and the radio frequency transmission channel and the radio frequency receiving channel.

[0010] In some embodiments, the data conversion module includes a dual-channel digital-to-analog converter and a dual-channel analog-to-digital converter, and is configured for mutual conversion between baseband digital signals and baseband analog signals.

[0011] In some embodiments, the processing system unit interacts with the programmable logic unit through a high-speed bus and communicates with a host computer through an external interface.

[0012] In a second aspect, the present application also provides a radar waveform adaptive optimization method, applied to the waveform optimization based adaptive environment cognition radar system as described in the first aspect, the radar waveform adaptive optimization method comprising: receiving the digital echo signal output via the radio frequency module; preprocessing the digital echo signal; performing a two-way parallel processing link operation on the preprocessed digital echo signal, the two-way parallel processing link operation comprising a first processing link operation and a second processing link operation; the first processing link operation comprises processing the preprocessed digital echo signal with a waveform optimization algorithm to dynamically generate an anti-interference waveform digital signal for the next transmission; wherein the waveform optimization algorithm is a closed-loop iterative algorithm based on environment perception and signal-to-clutter-and-noise ratio maximization criterion; the second processing link operation comprises outputting the preprocessed digital echo signal to the processing system unit for processing the preprocessed digital echo signal with a preset radar signal processing algorithm by the processing system unit.

[0013] In some embodiments, the processing of the preprocessed digital echo signal with a waveform optimization algorithm comprises: estimating the environmental interference spectral characteristics based on the preprocessed digital echo signal; iteratively calculating under the constraint of the transmission waveform constant modulus to maximize the system output signal-to-clutter-and-noise ratio as the optimization objective, to generate a signal energy spectrum allocation scheme; generating a corresponding time-domain waveform phase encoding sequence according to the signal energy spectrum allocation scheme as the waveform digital signal for the next transmission.

[0014] In some embodiments, the preprocessing of the digital echo signal comprises: performing pulse compression processing on the digital echo signal.

[0015] The embodiment of the present application realizes a cognitive radar closed loop by designing a parallel processing hardware architecture based on a programmable system-on-chip, realizes real-time processing of echoes and generation of optimized transmit waveforms through a programmable logic unit, forms a fast closed loop of perception, decision and action, enables the radar to interact with the environment, and significantly improves the real-time performance of the system, that is, the parallel processing capability of the programmable logic unit is used to process the waveform optimization task with high real-time requirement, the problem of high calculation delay of the traditional industrial computer architecture is solved, and the demand of electronic warfare for fast response is met. In addition, the resource utilization and system efficiency are optimized, the processing system unit and the programmable logic unit have clear division of labor, and parallelism does not contradict each other, so that the system can efficiently complete the two core tasks of waveform optimization and signal processing at the same time, and the overall processing efficiency and resource utilization rate are greatly improved. In summary, the embodiment of the present application efficiently realizes the core of the cognitive radar, that is, the real-time waveform optimization algorithm in the programmable logic unit, and executes the traditional signal processing algorithm on the processing system unit in parallel, provides a way for the real-time problem in the engineering application of the cognitive radar technology, and can significantly improve the survival ability and detection performance of the radar in a complex electromagnetic environment. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0017] Figure 1 is a circuit structure schematic diagram of an adaptive environment cognitive radar system based on waveform optimization provided by the present application.

[0018] Figure 2 is a flowchart of a radar waveform adaptive optimization method provided by the present application.

[0019] Figure 3 is a structure schematic diagram of a radar waveform adaptive optimization device provided by the present application.

[0020] Figure 4 is a physical structure schematic diagram of an electronic device provided by the present application. DETAILED DESCRIPTION

[0021] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the present application. Obviously, the described embodiments are only a 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 of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0022] The embodiment of the present application provides a waveform optimization based adaptive environment cognitive radar system and an optimization method. Figure 1 is a circuit structure schematic diagram of a waveform optimization based adaptive environment cognitive radar system provided by the present application. As shown in Figure 1 The waveform optimization based adaptive environment cognitive radar system comprises a radio frequency module 1 and a baseband signal processing module 2 connected with the radio frequency module 1. The baseband signal processing module 2 comprises a programmable system on chip integrated with a processing system unit 3 and a programmable logic unit 4. The programmable logic unit 4 is used for pre-processing a digital echo signal output via the radio frequency module 1, processing the pre-processed digital echo signal by using a waveform optimization algorithm to dynamically generate an anti-interference waveform digital signal, and outputting the waveform digital signal to the radio frequency module 1 for signal transmission next time. The waveform optimization algorithm is a closed loop iterative algorithm based on environment perception and signal to clutter and noise ratio maximization criterion. The processing system unit 3 can be connected with the programmable logic unit 4 through a self-defined bus. The processing system unit 3 is used for receiving the pre-processed digital echo signal output by the programmable logic unit 4, and processing the pre-processed digital echo signal by using a preset radar signal processing algorithm. The programmable logic unit 4 and the processing system unit 3 work in parallel to form a first processing link for dynamic waveform optimization and a second processing link for radar signal processing.

[0023] Specifically, the baseband signal processing module 2 is a hardware module responsible for radar baseband digital signal processing and control, and is specifically used for control instruction generation, radar signal processing, and data interaction. The baseband signal processing module 2 is composed of, for example, a ZYNQ series programmable system on chip. The programmable system on chip is a heterogeneous computing chip integrating a processing system unit 3, such as but not limited to an ARM (Advanced RISC Machines) processor, and a programmable logic unit 4, such as but not limited to a field programmable gate array (FPGA). Among them, the processing system unit 3 (PSU) refers to the processor core in the programmable system on chip, which is responsible for running the operating system and complex application programs. The programmable logic unit 4 (PLU) refers to the field programmable gate array part in the programmable system on chip, which is suitable for executing high-speed parallel digital signal processing tasks. The waveform optimization algorithm is an algorithm that can dynamically adjust the transmission waveform parameters according to the environmental feedback, and the goal is to improve the system output signal-to-noise ratio. The closed-loop iterative algorithm refers to the algorithm process containing a feedback loop, and the output will be used as the input for the next calculation, and the iteration will be continuously iterated to approach the optimal solution. The first processing link refers to the signal path completed in the programmable logic unit 4 for real-time waveform optimization processing. The second processing link refers to the signal path used for radar signal processing after the data is transmitted from the programmable logic unit 4 to the processing system unit 3.

[0024] A programmable system-on-chip integrated with a processing system unit 3 and a programmable logic unit 4 is adopted as the baseband signal processing module 2. The radio frequency module 1 outputs a digital echo signal to the programmable logic unit 4. The programmable logic unit 4 first pre-processes the digital echo signal, and then processes the pre-processed data using a closed-loop iterative algorithm based on the environment perception and signal-to-jamming-and-noise ratio maximization criterion, i.e., a waveform optimization algorithm. According to the perceived current environmental interference characteristics, the waveform optimization algorithm dynamically generates an anti-interference waveform digital signal, i.e., the digital form of the next transmission signal, and outputs it to the radio frequency module 1 for transmission. At the same time, the programmable logic unit 4 transmits the pre-processed digital echo signal to the processing system unit 3 in parallel through an internal high-speed bus. The processing system unit 3 is responsible for executing preset radar signal processing algorithms such as a constant false alarm rate detection algorithm and a target tracking algorithm. The programmable logic unit 4 and the processing system unit 3 work independently and cooperatively, forming a parallel double-processing link: the first processing link focuses on the dynamic real-time optimization of the transmission waveform; and the second processing link focuses on the traditional echo signal information extraction. This architecture enables the computationally intensive waveform optimization task to be completed at high speed in the programmable logic unit 4 without occupying the resources of the processing system unit 3, thereby ensuring the real-time performance of the entire cognitive closed loop. It should be noted that the specific implementation processes of the constant false alarm rate detection algorithm and the target tracking algorithm are well known to those skilled in the art, and will not be described here.

[0025] Traditional radars generally transmit a single type of waveform with fixed parameters, and use various signal processing techniques in the receiving link to obtain effective information and achieve accurate target acquisition. However, with the large-scale introduction of electronic jamming equipment and the increasingly complex battlefield environment, the traditional waveform transmission method has been difficult to meet the task requirements of target detection, tracking, etc. in a complex electromagnetic and non-uniform time-varying geographic environment. In the face of strong clutter interference in a complex weather environment, a fixed waveform may continuously transmit energy to a high-clutter frequency band, causing the signal-to-jamming-and-noise ratio at the receiving end to deteriorate sharply. Secondly, the signal processing process of a traditional radar is a one-way link, i.e., transmission, reception, and processing. The transmission end cannot obtain environmental feedback information, and the clutter interference suppression relies on the filtering algorithm at the receiving end, which cannot directly reduce the input of clutter energy. In addition, when encountering enemy jamming, the system needs to wait for manual intervention or preset strategy switching, which has a long response time and cannot meet the real-time requirements of modern electronic warfare scenarios.

[0026] In recent years, cognitive technology has become a research hotspot, that is, to enable radar systems to have the abilities of cognition, understanding, learning, inference and decision-making, and to continuously adjust the receiver and transmitter parameters to adapt to the complex detection environment, so as to realize the effective improvement of target detection, tracking and anti-jamming performance, which is the key technology of the next generation of intelligent radar systems. Compared with traditional radars, cognitive radar systems make full use of target and environment information, draw lessons from advanced optimization theory methods, and comprehensively consider the hardware resource constraints of radar systems, extend the adaptive mechanism from the receiving end to the transmitting end, build an adaptive processing architecture of the receiving channel, the transmitting channel and the dynamic closed loop of the environment, realize the dynamic optimization of the transmitting waveform, and enhance the detection performance of the radar system in the complex electromagnetic environment.

[0027] However, the existing system hardware is usually an open-loop architecture, that is, the preset fixed waveform is issued by an industrial computer, driven by a field programmable gate array to transmit the radio frequency front end, and the echo signal is returned to the field programmable gate array and the industrial computer, and then the subsequent processing such as clutter suppression and target detection is performed, which cannot support the cognitive radar technology mentioned in the above embodiments. In addition, the signal processing process of the traditional radar hardware architecture is mainly concentrated in the industrial computer, which is affected by the computing power, wideband signal transmission and the like, resulting in low system real-time performance. Therefore, it is urgent to build a new radar system hardware architecture to realize the cognitive radar technology of dynamic feedback, rapid decision-making and real-time optimization.

[0028] The embodiment of the present application realizes a real cognitive radar closed loop by designing a parallel processing hardware architecture based on a programmable system on chip, processes the echo in real time by the programmable logic unit 4 to generate an optimized transmitting waveform, forms a fast closed loop of perception, decision-making and action, enables the radar to interact with the environment, significantly improves the system real-time performance, processes the waveform optimization task with high real-time requirement by using the parallel processing capability of the programmable logic unit 4, solves the problem of high computing delay of the traditional industrial computer architecture, and meets the demand of rapid response in electronic warfare. In addition, the resource utilization and system efficiency are optimized, the processing system unit 3 and the programmable logic unit 4 have clear division of labor and are parallel, so that the system can efficiently complete the two core tasks of waveform optimization and signal processing at the same time, and the overall processing efficiency and resource utilization rate are greatly improved. In summary, the embodiment of the present application efficiently realizes the core of cognitive radar, that is, the real-time waveform optimization algorithm in the programmable logic unit 4, and executes it in parallel with the traditional signal processing algorithm on the processing system unit 3, which provides a way for the real-time problem in the engineering application of cognitive radar technology, and can significantly improve the survival ability and detection performance of the radar in the complex electromagnetic environment.

[0029] In some embodiments, the waveform optimization algorithm comprises: estimating the environmental interference spectral characteristics based on the pre-processed digital echo signals; performing iterative calculation under the constraint of constant modulus of the transmit waveform to maximize the system output signal-to-jamming-and-noise ratio as the optimization objective, to generate a signal energy spectrum allocation scheme; and generating a corresponding time-domain waveform phase coding sequence according to the signal energy spectrum allocation scheme as the waveform digital signal for the next transmission.

[0030] Specifically, the environmental interference spectral characteristics refer to the power distribution of the clutter and interference signals in the frequency domain in the environment. The signal energy spectrum allocation scheme refers to a scheme of how the transmit signal energy should be distributed on different frequency components. The time-domain waveform phase coding sequence corresponds to forming a specific waveform by controlling the phase value of the radar transmit signal at each time, and each value in the sequence represents a phase.

[0031] The execution of the waveform optimization algorithm in the programmable logic unit 4 contains three core steps. First, estimate the environmental interference spectral characteristics: the waveform optimization algorithm performs frequency domain analysis on the pre-processed digital echo signals, such as but not limited to Fourier transform and statistical processing, to calculate the power spectral density of the clutter and interference in the current environment. Second, generate a signal energy spectrum allocation scheme: the waveform optimization algorithm takes maximizing the system output signal-to-jamming-and-noise ratio as the mathematical objective function, and performs iterative optimization calculation under the constraint of constant total energy and constant modulus of the waveform. The output of this step is a theoretically optimal energy spectrum density, indicating which frequency bands the energy should be strengthened and which frequency bands the energy should be weakened to evade interference. Finally, synthesize the time-domain waveform: according to the optimal signal energy spectrum allocation scheme obtained in the previous step, a time-domain phase coding sequence is generated by, for example, an alternating projection algorithm. The amplitude of this sequence is constant to satisfy the constant modulus constraint, and its phase is carefully designed so that the spectrum of the waveform after transmission can approximate the theoretically optimal energy spectrum distribution.

[0032] Specifically, the system output signal-to-clutter-and-noise ratio is the ratio of target echo signal power to total power of clutter and noise. The higher the system output signal-to-clutter-and-noise ratio, the easier the target is to be detected and identified. In a complex environment, interference and clutter are the main problems. The fixed waveform may just emit energy to the strong clutter frequency band, causing the echo signal to be submerged. The embodiment of the present application optimizes the target to enable the radar to intelligently allocate energy, specifically through spectrum matching and constant modulus constraint. Spectrum matching, i.e. energy redistribution: the system estimates the spectrum distribution of clutter and interference in the environment by analyzing the preprocessed digital echo signal. After obtaining which frequency components interfere strongly, when transmitting the next waveform, reduce the energy emission in these interference frequency bands, and concentrate the energy in the frequency bands with weak interference. Constant modulus constraint is a very important hardware implementation constraint. The optimized waveform must be constant modulus in the time domain, i.e. the waveform amplitude at each time is constant, only the phase changes. The power amplifier of the radar can only work in the highest efficiency and best linearity state when driving a signal with constant amplitude. If a signal with varying amplitude is transmitted, the power amplifier will produce nonlinear distortion, which will seriously affect the performance. The constant modulus waveform ensures that the optimized waveform can be perfectly transmitted by the hardware.

[0033] Therefore, the embodiment of the present application realizes intelligent allocation of energy, allocates transmission energy based on the estimation of interference spectrum, actively avoids radiating energy to strong interference frequency bands, fundamentally reduces the input of clutter energy, improves the signal-to-clutter-and-noise ratio, and ensures the feasibility of the hardware, i.e. by strictly following the constant modulus constraint in optimization, it is ensured that the generated waveform digital signal can be efficiently and linearly amplified by the power amplifier in the later stage, avoiding signal distortion.

[0034] In some embodiments, the preprocessing includes pulse compression processing.

[0035] Specifically, the pulse compression processing mainly obtains high range resolution and signal-to-noise ratio output by transmitting a wide pulse signal, for example but not limited to, through phase or frequency modulation, and performing matched filtering processing at the receiving end. In the programmable logic unit 4, the digital echo signal output by the radio frequency module 1 is preprocessed, i.e. pulse compression processing. This processing performs convolution operation on the digital echo signal through a digital filter matched with the conjugate of the transmitted signal. This operation can compress the pulse width of the digital echo signal, significantly improve the range resolution of the radar, and greatly improve the signal-to-noise ratio of the digital echo signal, providing a higher quality signal basis for the subsequent waveform optimization algorithm and target detection. It should be noted that the specific implementation process of pulse compression processing is well known to those skilled in the art, which will not be described here.

[0036] Therefore, this embodiment of the invention significantly improves the signal-to-noise ratio of the digital echo signal by utilizing pulse compression processing, resulting in more accurate estimation of environmental interference characteristics and enhancing the effectiveness of the waveform optimization algorithm. Furthermore, it improves range resolution, enabling the radar to distinguish between two closer targets and enhancing system performance.

[0037] In some embodiments, the radio frequency module 1 includes a radio frequency signal processing module 5, an intermediate frequency signal processing module 6, and a data conversion module 7; the waveform digital signal generated by the programmable logic unit 4 is processed sequentially by the digital to analog converter (DAC) in the data conversion module 7, the intermediate frequency transmission channel in the intermediate frequency signal processing module 6, and the radio frequency transmission channel in the radio frequency module 1, and then transmitted by the antenna.

[0038] Specifically, the antenna, RF signal processing module 5, intermediate frequency signal processing module 6, data conversion module 7, and baseband signal processing module 2 are connected in sequence, and all of the aforementioned modules are connected to the power supply module. The antenna is used to transmit and receive RF signals. The RF signal processing module 5 is used for frequency conversion and amplitude conditioning between the intermediate frequency signal and the RF signal.

[0039] In some embodiments, the radio frequency signal processing module 5 includes a circulator, a radio frequency transmitting channel, a radio frequency receiving channel, and a first local oscillator signal source. The circulator is used for directional signal transmission and full-duplex transmission and reception between the antenna and the radio frequency transmitting channel and the radio frequency receiving channel.

[0040] Specifically, the radio frequency receiving channel, i.e. Figure 1 The lower half of the circuit in the radio frequency signal processing module 5 shown includes a component consisting of... Figure 1 From right to left, the following components are connected in sequence: an RF bandpass filter, a low-noise amplifier, and a mixer; the RF transmit channel. Figure 1 The upper part of the RF signal processing module 5 shown includes the circuitry composed of... Figure 1 From left to right, the following components are connected in sequence: an intermediate frequency amplifier, a mixer, an RF bandpass filter, and a power amplifier. A circulator connects the RF transmit and receive channels to the antenna, enabling directional signal transmission and full-duplex transmission / reception. The first local oscillator signal source uses a phase-locked loop and a power divider to provide RF local oscillator signals to the transmit and receive channels respectively. The circulator is a non-reciprocal multiport microwave device used to achieve directional signal transmission; here, it isolates the transmit and receive channels, allowing both to share a single antenna. Full-duplex transmission / reception means that radar transmit and receive functions can be performed simultaneously or alternately without mutual interference.

[0041] A circulator is a key component for achieving full-duplex radio frequency (RF) transmission and reception. It typically has three ports: one connected to the output of the RF transmit channel, one to the antenna, and one to the input of the RF receive channel. Its characteristic is that signals can only be transmitted in a specific order. Figure 1The arrow direction clockwise transmission, and can not be transmitted in reverse. Therefore, the high-power transmission signal from the transmitting channel enters the port A1, and then flows from the port A2 to the antenna and radiates out. While the weak echo signal enters the port A2 from the antenna, it is guided to the port A3 into the receiving channel, thereby effectively preventing the high-power transmission signal from directly entering the sensitive receiving channel and causing it to burn out. Thus, the antenna sharing is realized, and the transmitting and receiving are shared by one antenna through the circulator, which simplifies the system structure, reduces the cost and volume. The transmitting and receiving channels are effectively isolated, the expensive receiving front-end components such as low-noise amplifiers are protected, and the reliability and life of the system are improved.

[0042] The intermediate frequency signal processing module 6 is a hardware component responsible for frequency conversion and amplitude conditioning between intermediate frequency signals and baseband signals. Similar to the radio frequency signal processing module 5, the intermediate frequency signal processing module 6 is used for frequency conversion and amplitude conditioning between intermediate frequency analog signals and baseband analog signals, including an intermediate frequency transmitting channel, an intermediate frequency receiving channel, and a second local oscillator signal source. The intermediate frequency receiving channel, i.e. Figure 1 The lower half of the circuit in the intermediate frequency signal processing module 6 shown includes an intermediate frequency bandpass filter, a fixed gain amplifier, a demodulator, a baseband low pass filter, and a variable gain amplifier connected in sequence from right to left. The intermediate frequency transmitting channel, i.e. Figure 1 The lower half of the circuit in the intermediate frequency signal processing module 6 shown includes an intermediate frequency bandpass filter, a fixed gain amplifier, a demodulator, a baseband low pass filter, and a variable gain amplifier connected in sequence from right to left. The intermediate frequency transmitting channel, i.e. Figure 1 The upper half of the circuit in the intermediate frequency signal processing module 6 shown includes a baseband low pass filter, a baseband fixed gain amplifier, a modulator, and an intermediate frequency bandpass filter connected in sequence from left to right. The second local oscillator signal source provides intermediate frequency local oscillator signals for the modulator and the demodulator. Figure 1 The upper half of the circuit in the intermediate frequency signal processing module 6 shown includes a baseband low pass filter, a baseband fixed gain amplifier, a modulator, and an intermediate frequency bandpass filter connected in sequence from left to right. The second local oscillator signal source provides intermediate frequency local oscillator signals for the modulator and the demodulator.

[0043] In some embodiments, the data conversion module 7 includes a dual-channel digital-to-analog converter 12 and a dual-channel analog-to-digital converter 13 (Analog to Digital Converter, ADC), and the data conversion module 7 is used for mutual conversion between baseband digital signals and baseband analog signals.

[0044] Specifically, the dual-channel digital-to-analog converter 12 is a device that can simultaneously convert two digital signals into two analog signals. The dual-channel analog-to-digital converter 13 is a device that can simultaneously convert two analog signals into two digital signals. In modern radar systems, quadrature modulation and demodulation technology is usually used. The dual-channel digital-to-analog converter 12 in the data conversion module 7 is responsible for converting the two quadrature waveform digital signals generated by the programmable logic unit 4 into analog baseband signals. Similarly, the dual-channel analog-to-digital converter 13 is responsible for converting the two quadrature baseband analog signals sent by the intermediate frequency processing module into digital signals for processing by the programmable logic unit 4. This quadrature processing can preserve the phase information of the signal, which is crucial for complex waveform optimization.

[0045] Thus, the embodiment of the present application supports complex signal processing, the dual-channel structure supports the conversion of quadrature signals, provides a hardware basis for generating and processing complex phase-coded waveforms, is a necessary condition for implementing advanced waveform optimization algorithms, retains complete signal information, and through simultaneously processing two quadrature signals, completely retains the amplitude and phase information of a digital echo signal, and provides sufficient data basis for environment cognition.

[0046] In summary, the waveform optimization module of the programmable logic unit 4 generates an optimized waveform digital signal, i.e., a set of phase codes, which is converted into an analog signal by the dual-channel digital-to-analog converter 12. The analog signal enters the intermediate frequency transmitting channel, is filtered and amplified, and is modulated with an intermediate frequency local oscillator signal, i.e., is up-converted into an intermediate frequency signal. The intermediate frequency signal enters the radio frequency transmitting channel and is amplified again, and is mixed with a radio frequency local oscillator signal, i.e., is up-converted into a higher radio frequency signal, which is amplified by a power amplifier and is transmitted by an antenna.

[0047] The antenna receives a weak echo signal reflected by a target, and the echo signal enters the radio frequency receiving channel through the circulator. The echo signal is first amplified by a low-noise amplifier, and is then mixed with a radio frequency local oscillator signal, i.e., is down-converted into an intermediate frequency signal. The intermediate frequency signal enters the intermediate frequency receiving channel, is filtered and amplified, and is demodulated with an intermediate frequency local oscillator signal, i.e., is down-converted into a baseband analog signal. The baseband analog signal is high-speed sampled by the dual-channel analog-to-digital converter 13, is converted back into a digital signal, and is sent back to the programmable logic unit 4.

[0048] After receiving the digital echo signal, the programmable logic unit 4 uses its parallel processing capability to perform pulse compression, i.e., matching filtering and other preprocessing operations, to preliminarily improve the signal-to-noise ratio. The preprocessed data is divided into two paths: one path corresponds to a fast cognition loop, and the data is sent to the cognition waveform optimization module in the programmable logic unit 4. The module immediately performs the SCNR maximization optimization algorithm based on the latest echo data. Since all calculations are completed in parallel by hardware logic in the programmable logic unit 4, the speed is extremely fast, and the next optimal waveform can be calculated within microseconds or milliseconds, and is immediately sent to the transmitting chain for the next transmission. This realizes a fast closed loop of receiving, analyzing, optimizing, and transmitting. The other path corresponds to a traditional processing loop, and the data is transmitted to the processing system unit 3 through a high-speed bus. The processing system unit 3 runs an operating system and more complex application programs, and performs more advanced and computationally intensive algorithms such as constant false alarm detection, target tracking, and identification. The processing results can be uploaded to an industrial computer through an optical fiber for display and control. It should be noted that the internal components and connection relationships of the above modules are well known to those skilled in the art, and will not be described here.

[0049] In some embodiments, the processing system unit 3 interacts with the programmable logic unit 4 through a high-speed bus, and communicates with an upper computer through an external interface.

[0050] Specifically, the high-speed bus refers to an internal communication channel for high-speed data interaction between the programmable logic unit 4 and the processing system unit 3. The external interface refers to the interface for communication between the processing system unit 3 and the external host computer. Inside the programmable system-on-chip, the transmission of the preprocessed echo data from the programmable logic unit 4 to the processing system unit 3 is completed through the high-speed bus inside the chip. This bus is specially designed for high-speed data transmission, with extremely low delay and high bandwidth, ensuring the data throughput of the second processing link. After the processing system unit 3 completes the signal processing, it will upload the target detection results, tracking track data, etc. to the external host computer through the external interface for display, recording and higher-level command and control.

[0051] Therefore, the embodiment of the present application ensures the internal communication efficiency, and the high-speed bus guarantees the real-time data interaction between the parallel double processing links, which is the basis for the cooperative work of the whole system. A flexible external interaction is provided, and the standard external interface enables the system to be easily integrated into the existing radar system or test environment, enhancing the versatility and scalability of the system.

[0052] In some embodiments, the cognitive radar system performs waveform iterative optimization as follows: in the programmable logic unit 4, the cognitive waveform optimization module outputs a digital signal corresponding to the waveform. After the digital signal is converted into an analog signal by the double-channel digital-to-analog converter 12 in the data conversion module 7, it is input into the intermediate frequency transmission channel of the intermediate frequency signal processing module 6, and after amplitude conditioning, quadrature modulation and filtering processing, an intermediate frequency transmission signal is obtained. The intermediate frequency transmission signal enters the radio frequency transmission channel, and after intermediate frequency amplification, up-conversion, radio frequency filtering and power amplification, a radio frequency transmission signal is obtained, which is radiated into space through a circulator and an antenna. The radio frequency receiving end captures the target echo signal through the antenna, and after passing through the circulator, it enters the radio frequency receiving channel for pre-selection filtering, low-noise amplification and down-conversion to obtain an intermediate frequency receiving signal. After filtering, fixed gain amplification, quadrature demodulation, baseband filtering and variable gain amplification, a baseband receiving signal is obtained, which is discretized by the double-channel analog-to-digital converter 13 to obtain a digital echo signal, which is then input into the programmable logic unit 4 of the baseband signal processing module 2. The programmable logic unit 4 performs pulse compression and other signal preprocessing procedures through high-speed parallel operation. The preprocessed signal is divided into two paths, one of which is input into the programmable logic unit 4 to obtain an energy spectrum allocation scheme based on the maximum SCNR cognitive waveform optimization module, and the time domain representation of the optimal waveform under the constant modulus constraint is obtained and sent to the transmitting end. The other signal is input into the processing system unit 3 through the self-defined bus, and subsequent radar signal processing algorithms are executed, and the interaction between the processing system unit 3 and the host computer and other external devices is realized through optical fiber.

[0053] Compared with a traditional radar signal processing procedure, the environment adaptive cognitive radar system provided in the embodiment of the present application realizes the cognition of a complex electromagnetic environment through optimizing iterative transmission waveforms, that is, around the original echo signal received by the programmable logic unit 4, an optimal signal energy spectrum distribution scheme is dynamically designed based on the maximization of SCNR, and a constant modulus time domain waveform is generated as the next transmission waveform by considering the influence of the hardware itself nonlinearity, thereby realizing the closed-loop cognition of receiving-analysis-optimization-transmission. In addition, in combination with the above procedure, the hardware implementability is fully considered, the programmable logic unit 4 of the programmable system on chip ZYNQ is used to realize the waveform optimization closed-loop processing, and the preprocessed echo signal is sent to the processing system unit 3 for subsequent radar signal processing procedures, thereby forming the dual-path parallel architecture of the dynamic waveform optimization of the programmable logic unit 4 and the radar signal processing of the processing system unit 3, reducing the influence of the data transmission between the programmable logic unit 4 and the processing system unit 3 on the real-time performance, and providing strong support for radar target detection in a complex electromagnetic environment.

[0054] In summary, the adaptive environment cognitive radar system based on waveform optimization provided in the embodiment of the present application mainly includes the following two innovative points: first, the hardware characteristics are fully considered, the closed-loop feedback mechanism of the radar system and the external environment is constructed, the transmission signal spectrum is dynamically adjusted based on the programmable logic unit 4 under the constant modulus constraint with the maximization of SCNR as the target, the adaptive redistribution of the transmission signal energy is realized, and thus various interferences in the complex electromagnetic environment are effectively suppressed. Second, the parallel computing architecture of the programmable logic unit 4-processing system unit 3 cooperative processing is adopted, the programmable logic unit 4 performs the echo signal preprocessing and the waveform iterative optimization of the environment cognition, and the preprocessed data is transmitted to the processing system unit 3 to perform the subsequent radar signal processing algorithm, thereby improving the real-time performance of the cognitive radar system.

[0055] The present application further provides a radar waveform adaptive optimization method. Figure 2 The radar waveform adaptive optimization method provided by the present application is applied to the adaptive environment cognitive radar system based on waveform optimization as described in the above embodiment, and can be executed by the radar waveform adaptive optimization device provided by the embodiment of the present application. The radar waveform adaptive optimization device can be realized in the form of software and / or hardware, and can be integrated in the programmable logic unit of the baseband signal processing module. As shown in the figure, the radar waveform adaptive optimization method includes the following steps: Figure 2 Step 101, receiving the digital echo signal output via the radio frequency module.

[0056] Step 102, preprocessing the digital echo signal.

[0057] ​Step 103, performing two parallel processing link operations on the preprocessed digital echo signal.

[0058] The two parallel processing link operations include a first processing link operation and a second processing link operation. The first processing link operation includes processing the preprocessed digital echo signal by using a waveform optimization algorithm to dynamically generate an anti-interference waveform digital signal for the next transmission; wherein the waveform optimization algorithm is a closed-loop iterative algorithm based on environmental perception and signal-to-jamming noise ratio maximization criteria; and the second processing link operation includes outputting the preprocessed digital echo signal to a processing system unit for processing the preprocessed digital echo signal by the processing system unit using a preset radar signal processing algorithm.

[0059] Specifically, the repeated part of the radar waveform adaptive optimization method can be understood with reference to the description of the above embodiments, which will not be repeated here. The two parallel processing link operations refer to the operation mode of simultaneously performing two different processing on the same preprocessed data.

[0060] The radar waveform adaptive optimization method describes the core process in the programmable logic unit during system operation. After receiving the digital echo signal and completing the preprocessing, the process is divided into two parallel executions. The first processing link operation: the preprocessed data is sent to the waveform optimization algorithm module. Based on the perceived environmental information, the algorithm dynamically calculates the next transmission waveform digital signal with better anti-interference performance. The second processing link operation: the same preprocessed data is sent to the processing system unit through the high-speed bus. The processing system unit independently runs its preset radar signal processing algorithm to extract target information from the echo. The two operations are performed simultaneously and do not wait for each other, fully embodying the efficiency improvement brought by the hardware parallel architecture.

[0061] In some embodiments, processing the preprocessed digital echo signal by using the waveform optimization algorithm includes: estimating the environmental interference spectral characteristics based on the preprocessed digital echo signal; performing iterative calculation under the constraint of the transmission waveform constant modulus to generate a signal energy spectrum allocation scheme with the maximum system output signal-to-jamming noise ratio as the optimization target; and generating a corresponding time-domain waveform phase encoding sequence according to the signal energy spectrum allocation scheme as the waveform digital signal for the next transmission. For details, please refer to the above embodiments, which will not be repeated here.

[0062] In some embodiments, the preprocessing of the digital echo signal includes pulse compression processing of the digital echo signal. For details, please refer to the above embodiments, which will not be repeated here.

[0063] The waveform optimization algorithm refers to an iterative calculation process based on echo signal sensing the environment and aiming to maximize the output signal-to-clutter-and-noise ratio. The core of the algorithm is to dynamically adjust the energy spectrum distribution of the next transmitted waveform according to the spectral characteristics of the environmental interference, and to synthesize the time-domain waveform under the constant modulus constraint. The closed-loop iterative algorithm refers to the output of the waveform optimization algorithm, i.e., the waveform digital signal, which will be used for the next transmission. The echo generated thereby will be used as the new input of the algorithm, thereby forming a closed-loop system that continuously senses and optimizes.

[0064] First, signal reception and preprocessing: the target echo signal received by the radio frequency front end is converted into a digital echo signal after down-conversion and analog-to-digital conversion, and is input to the programmable logic unit. In the programmable logic unit, the digital echo signal is first preprocessed, and the most critical step is pulse compression processing. Pulse compression is achieved by passing the echo signal through a digital filter whose transfer function is conjugate matched to the transmitted signal. This processing significantly improves the signal-to-noise ratio and range resolution of the echo signal, laying a signal foundation for subsequent accurate environmental sensing.

[0065] Second, environmental sensing and interference estimation: the preprocessed data contains mixed information of targets, clutter, and noise. The waveform optimization algorithm first needs to estimate the spectral characteristics of the environmental interference from these data. Specifically, the algorithm performs frequency domain transformation, such as fast Fourier transform and statistical averaging, on the preprocessed data, such as selecting the clutter-dominated range cells, to calculate the energy spectrum density of the clutter and interference in the current detection environment. The purpose of this step is to quantify the severity of the environment in the frequency domain, i.e., to determine which frequency bands need to be avoided due to strong interference and which frequency bands can be utilized due to relatively clean.

[0066] The most core is the optimal energy spectrum calculation: after obtaining the environmental interference characteristics, the algorithm optimizes the calculation with the goal of maximizing the system output signal-to-clutter-and-noise ratio. This is a constrained optimization process, the mathematical essence of which is to solve the energy spectrum density of the transmitted waveform that maximizes the signal-to-clutter-and-noise ratio under the constraints of constant total transmitted energy and constant modulus of the transmitted waveform. Exemplarily, the water-filling principle can be used for solution, and constant modulus time-domain waveform synthesis is performed: the optimal energy spectrum density obtained in the previous step is a frequency domain function. The goal of this step is to generate a time-domain waveform whose amplitude must be constant and whose energy spectrum must be as close as possible to the optimal energy spectrum calculated in the previous step. This is a phase recovery problem, which can be solved exemplarily by using the alternating projection algorithm, which includes: The first step, frequency domain projection, starts with an initial constant-mode signal (random phase), calculates its Fourier transform, and then replaces its spectral amplitude with the amplitude specified by the optimal energy spectral density, while preserving its phase. This step projects the signal onto a set of signals with the desired energy spectrum. The second step, time domain projection, performs an inverse Fourier transform back to the time domain on the frequency-domain projected signal, then forces the amplitude of the time-domain signal to be constant, setting the amplitude value at each moment to a constant value and retaining only its phase information. This step projects the signal back into a set of constant-mode signals.

[0067] Repeat steps one and two iteratively. Each iteration brings the energy spectrum of the generated time-domain constant-modulus signal closer to the optimal energy spectrum. After a predetermined number of iterations, the final time-domain waveform phase-coded sequence is output as the waveform digital signal for the next transmission. It should be noted that the specific implementation processes of the water-filling method, alternating projection algorithm, fast Fourier transform, and statistical averaging algorithms described in the above embodiments are well known to those skilled in the art and will not be elaborated upon here.

[0068] The radar waveform adaptive optimization device provided by the present invention is described below. The radar waveform adaptive optimization device described below can be referred to in correspondence with the radar waveform adaptive optimization method described above. Figure 3 This is a schematic diagram of the structure of a radar waveform adaptive optimization device provided by the present invention. Figure 3 As shown, the radar waveform adaptive optimization device includes a signal receiving module 201 for receiving digital echo signals output from the radio frequency module; a preprocessing module 202 for preprocessing the digital echo signals; and a parallel processing module 203 for performing two parallel processing link operations on the preprocessed digital echo signals. The first processing link operation includes processing the preprocessed digital echo signals using a waveform optimization algorithm to dynamically generate anti-interference waveform digital signals for the next transmission. The waveform optimization algorithm is a closed-loop iterative algorithm based on environmental perception and the maximization of signal-to-clutter-to-noise ratio. The second processing link operation includes outputting the preprocessed digital echo signals to a processing system unit, which then processes the preprocessed digital echo signals using a preset radar signal processing algorithm.

[0069] Figure 4 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. For example... Figure 4As shown, the electronic device can include a processor 301, a communications interface 302, a memory 303, and a communications bus 304, wherein the processor 301, the communications interface 302, and the memory 303 complete mutual communication through the communications bus 304. The processor 301 can invoke a logic instruction in the memory 303 to execute a radar waveform adaptive optimization method, which includes: receiving a digital echo signal output via a radio frequency module; preprocessing the digital echo signal; performing a two-way parallel processing link operation on the preprocessed digital echo signal; The first processing link operation includes processing the preprocessed digital echo signal using a waveform optimization algorithm to dynamically generate an anti-interference waveform digital signal for the next transmission; wherein the waveform optimization algorithm is a closed-loop iterative algorithm based on environment perception and signal-to-noise ratio maximization criteria; The second processing link operation includes outputting the preprocessed digital echo signal to a processing system unit to process the preprocessed digital echo signal using a preset radar signal processing algorithm by the processing system unit.

[0070] In addition, the logic instruction in the memory 303 described above can be implemented in the form of a software function 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 the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the 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 program code storage media.

[0071] On the other hand, the present application 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, and the computer program is executed by a processor, the computer can execute the radar waveform adaptive optimization method provided by the above-mentioned embodiments, which includes: receiving a digital echo signal output via a radio frequency module; preprocessing the digital echo signal; performing two parallel processing link operations on the preprocessed digital echo signal; The first processing link operation comprises processing the preprocessed digital echo signal by using a waveform optimization algorithm to dynamically generate an anti-interference waveform digital signal for the next transmission; wherein the waveform optimization algorithm is a closed-loop iterative algorithm based on environment perception and signal-to-jamming noise ratio maximization criterion; The second processing link operation comprises outputting the preprocessed digital echo signal to a processing system unit to process the preprocessed digital echo signal by the processing system unit using a preset radar signal processing algorithm.

[0072] In yet another aspect, the present application also provides a non-transitory computer readable storage medium having stored thereon a computer program, which, when executed by a processor, implements the radar waveform adaptive optimization method provided by the above-mentioned embodiments, and the method comprises: receiving a digital echo signal output via a radio frequency module; preprocessing the digital echo signal; performing two parallel processing link operations on the preprocessed digital echo signal; The first processing link operation comprises processing the preprocessed digital echo signal by using a waveform optimization algorithm to dynamically generate an anti-interference waveform digital signal for the next transmission; wherein the waveform optimization algorithm is a closed-loop iterative algorithm based on environment perception and signal-to-jamming noise ratio maximization criterion; The second processing link operation comprises outputting the preprocessed digital echo signal to a processing system unit to process the preprocessed digital echo signal by the processing system unit using a preset radar signal processing algorithm.

[0073] The device embodiments described above are merely illustrative, wherein the units illustrated as separate components can or can not be physically separated, and the components illustrated as units can or can not be physical units, i.e., they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected to achieve the purposes of the present embodiment scheme according to actual needs. Those skilled in the art can understand and implement it without creative labor.

[0074] Those skilled in the art can clearly understand the implementation of the various embodiments by means of software and necessary general hardware platforms through the description of the above embodiments, and of course, the implementation can also be through hardware. Based on such understanding, the above technical solutions 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 a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the method of each embodiment or some parts of the embodiment.

[0075] Finally, it should be noted that: the above examples 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 examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for some technical features thereof; 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 waveform-optimization-based adaptive environmental cognition radar system, characterized in that, The radar waveform adaptive optimization method comprises the following steps: receiving a digital echo signal output via a radio frequency module; preprocessing the digital echo signal; performing two-way parallel processing link operations on the preprocessed digital echo signal, the two-way parallel processing link operations comprising a first processing link operation and a second processing link operation; the first processing link operation comprises using a waveform optimization algorithm to process the preprocessed digital echo signal to dynamically generate an anti-interference waveform digital signal for the next transmission; wherein the waveform optimization algorithm is a closed-loop iterative algorithm based on environmental perception and signal-to-jamming noise ratio maximization criterion; 2. The waveform-optimization-based adaptive environmental cognition radar system of claim 1, wherein, the second processing link operation comprises using a preset radar signal processing algorithm to process the preprocessed digital echo signal. The waveform optimization algorithm comprises the following steps: estimating environmental interference spectral characteristics based on the preprocessed digital echo signal; iteratively calculating under the constraint of transmission waveform constant modulus to generate a signal energy spectrum allocation scheme, with the optimization objective of maximizing the system output signal-to-jamming noise ratio; 3. The waveform-optimization-based adaptive environmental cognition radar system of claim 1, wherein, generating a corresponding time-domain waveform phase encoding sequence as the waveform digital signal for the next transmission according to the signal energy spectrum allocation scheme.

4. The waveform-optimization-based adaptive environmental cognition radar system according to any one of claims 1-3, characterized in that, The preprocessing comprises pulse compression processing. The radio frequency module comprises a radio frequency signal processing module, an intermediate frequency signal processing module, and a data conversion module; 5. The waveform-optimization-based adaptive environmental cognition radar system of claim 4, wherein, the waveform digital signal generated by the programmable logic unit is processed by a digital-to-analog converter in the data conversion module, an intermediate frequency transmission channel in the intermediate frequency signal processing module, and a radio frequency transmission channel in the radio frequency module in sequence, and then transmitted by an antenna.

6. The waveform optimization based adaptive environmental cognition radar system of claim 4, wherein, The radio frequency signal processing module comprises a circulator, a radio frequency transmission channel, a radio frequency receiving channel, and a first local oscillator signal source, and the circulator is used for signal directional transmission and transceiver duplex between the antenna and the radio frequency transmission channel and the radio frequency receiving channel.

7. The waveform-optimization-based adaptive environmental cognition radar system according to any one of claims 1-3, characterized in that, The data conversion module comprises a double-channel digital-to-analog converter and a double-channel analog-to-digital converter, and is used for mutual conversion between baseband digital signals and baseband analog signals.

8. A radar waveform adaptive optimization method applied to the waveform optimization based adaptive environment aware radar system according to any one of claims 1-7, characterized in that, The processing system unit interacts with the programmable logic unit through a high-speed bus and communicates with an upper computer through an external interface. The radar waveform adaptive optimization method comprises the following steps: receiving a digital echo signal output via a radio frequency module; preprocessing the digital echo signal; performing two-way parallel processing link operations on the preprocessed digital echo signal, the two-way parallel processing link operations comprising a first processing link operation and a second processing link operation; the first processing link operation comprises using a waveform optimization algorithm to process the preprocessed digital echo signal to dynamically generate an anti-interference waveform digital signal for the next transmission; wherein the waveform optimization algorithm is a closed-loop iterative algorithm based on environmental perception and signal-to-jamming noise ratio maximization criterion; the second processing link operation comprises using a preset radar signal processing algorithm to process the preprocessed digital echo signal. The second processing link operation comprises outputting the preprocessed digital echo signal to the processing system unit for processing the preprocessed digital echo signal by the processing system unit using a preset radar signal processing algorithm.

9. The radar waveform adaptive optimization method of claim 8, wherein, The processing of the preprocessed digital echo signal using the waveform optimization algorithm comprises: estimating environmental interference spectral characteristics based on the preprocessed digital echo signal; iteratively calculating under a constant modulus constraint of a transmit waveform to generate a signal energy spectrum allocation scheme, with a maximum system output signal-to-jamming-and-noise ratio as an optimization objective; generating a corresponding time-domain waveform phase encoding sequence as the waveform digital signal for the next transmission according to the signal energy spectrum allocation scheme.

10. The radar waveform adaptive optimization method of claim 8 or 9, wherein, The preprocessing of the digital echo signal comprises: pulse compression processing of the digital echo signal.

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