Surrounding environment target sensing method and system based on millimeter wave radar

Abstract

The invention relates to a surrounding environment target sensing method and system based on a millimeter wave radar. The method comprises the following steps: sending a detection signal to a surrounding environment and obtaining a feedback signal; determining a target sensing object included in the feedback signal and continuously tracking the target sensing object; when the non-distance signal intensity of the target sensing object signal changes, calculating a sidelobe ratio in a feedback signal corresponding to the target sensing object; when the change intensity of the sidelobe ratio exceeds an allowable change range or the duration of the change intensity of the sidelobe ratio exceeds a set time, reanalyzing other sidelobes in the feedback signal, and determining whether a hidden sensing object exists in the suppressed sidelobe signal; according to the surrounding environment target sensing method and system based on the millimeter wave radar, the sidelobe signal in the feedback signal is dynamically processed in a signal intensity analysis mode, so that a real target hidden in the sidelobe signal is found.

Description

Technical Field

[0001] This application relates to the technical field of signal processing, and in particular, to a method and system for surrounding environment target perception based on a millimeter-wave radar. Background Art

[0002] A millimeter-wave radar (the wavelength of the electromagnetic wave used belongs to the millimeter range) is a radar that uses electromagnetic waves with a wavelength of 1–10 millimeters (frequency of 30–300 GHz) for target detection, and has the characteristics of short wavelength and high frequency.

[0003] When a millimeter-wave radar perceives surrounding environment targets, false targets will be generated when it is deceived, and these targets will directly affect the judgment ability of the millimeter-wave radar. Especially when using high-power interference means, real targets in the surrounding environment are likely to be hidden in the sidelobes of the received signal, resulting in these real targets not being detected. Summary of the Invention

[0004] This application provides a method and system for surrounding environment target perception based on a millimeter-wave radar, which dynamically processes the sidelobe signals in the feedback signal through signal intensity analysis to discover real targets hidden in the sidelobe signals.

[0005] The above object of this application is achieved through the following technical solutions: In a first aspect, this application provides a method for surrounding environment target perception based on a millimeter-wave radar, including: Sending a detection signal into the surrounding environment and obtaining a feedback signal; Analyzing the feedback signal to determine the target perception objects included in the feedback signal and continuously tracking the target perception objects; Calculating the signal intensity of the target perception object. When the non-distance signal intensity of the target perception object signal changes, calculating the sidelobe ratio in the feedback signal corresponding to the target perception object; When the change intensity of the sidelobe ratio exceeds the allowable change range or the duration of the change intensity of the sidelobe ratio exceeds the set time, re-analyzing other sidelobes in the feedback signal to determine whether there are hidden perception objects in the suppressed sidelobe signals.

[0006] In a possible implementation manner of the first aspect, when continuously tracking the target perception object, the detection signal is adjusted using a dynamic slope method, and the dynamic slope method for adjusting the detection signal includes slope adjustment and duration adjustment; When adjusting the detection signal using the dynamic slope method, at least one of the temperature parameter, environmental noise parameter, detection signal parameter, and feedback signal parameter is used as basic data and input into a random number generator to generate a random number sequence, and slope adjustment parameters and duration adjustment parameters are selected from the random number sequence.

[0007] In a possible implementation of the first aspect, when adjusting the detection signal using the dynamic slope method, it further includes calculating the proportion of clutter signal energy in the feedback signal and dynamically adjusting the slope adjustment parameters according to the proportion of clutter signal energy; The dynamic adjustment parameter of the slope adjustment parameter is related to the proportion of clutter signal energy in the feedback signal; When dynamically adjusting the slope adjustment parameters, the receiving intensity of the receiver is less than the saturation receiving intensity; Antennas located in the same matrix use the same slope adjustment parameters and duration adjustment parameters.

[0008] In a possible implementation of the first aspect, when calculating the sidelobe ratio in the feedback signal corresponding to the target sensing object, it further includes: Inserting a random phase lag amount into the detection signal; Comparing the spectrum before the insertion of the random phase lag amount and the spectrum after the insertion of the random phase lag amount, and determining the overlapping time between the peaks; Adjusting the random phase lag amount according to the overlapping time to make the overlapping time between the peaks tend to zero.

[0009] In a possible implementation of the first aspect, re-analyzing other sidelobes in the feedback signal includes: Selecting two detection signals in the time series, and inserting a random phase lag amount into at least one of the two detection signals; Determining the sidelobes with height changes; Performing correlation processing on the sidelobes with height changes; Determining whether there are hidden sensing objects according to the correlation processing results.

[0010] In a possible implementation of the first aspect, performing correlation processing on the sidelobes with height changes includes: Determining the height change value of the sidelobes with height changes; Performing correlation processing on the sidelobes with height changes according to the height change value. During the correlation processing, each height change value can be used as the main lobe height.

[0011] In a possible implementation of the first aspect, after obtaining the hidden sensing object, it further includes: Continuously tracking the existing hidden sensing objects in the time series; Determine the existence time of the hidden perception object in the time series; Perform retention processing and deletion processing on the hidden perception object according to the existence time.

[0012] In a second aspect, the present application provides a surrounding environment target perception device based on a millimeter-wave radar, which adopts the method described in the first aspect and any possible implementation manner of the first aspect, including: A signal transceiver unit for sending a detection signal to the surrounding environment and obtaining a feedback signal; A signal processing unit for analyzing the feedback signal, determining the target perception object included in the feedback signal, and continuously tracking the target perception object; A signal calculation unit for calculating the signal strength of the target perception object, and when the non-distance signal strength of the target perception object signal changes, calculating the sidelobe ratio in the feedback signal corresponding to the target perception object; A signal reprocessing unit for re-analyzing other sidelobes in the feedback signal to determine whether there is a hidden perception object in the suppressed sidelobe signal when the change intensity of the sidelobe ratio exceeds the allowable change range or the duration of the change intensity of the sidelobe ratio exceeds the set time.

[0013] In a third aspect, the present application provides a surrounding environment target perception system based on a millimeter-wave radar, and the system includes: One or more memories for storing instructions; One or more processors for calling and running the instructions from the memory and executing the method described in the first aspect and any possible implementation manner of the first aspect.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, and the computer-readable storage medium stores a program, and when the program is run by a processor, the method described in the first aspect and any possible implementation manner of the first aspect is executed.

[0015] In a fifth aspect, the present application provides a computer program product, including program instructions, and when the program instructions are run by a computing device, the method described in the first aspect and any possible implementation manner of the first aspect is executed.

[0016] In a sixth aspect, the present application provides a chip system, and the chip system includes a processor for implementing the functions involved in the above aspects, for example, generating, receiving, sending, or processing the data and / or information involved in the above method.

[0017] The chip system may be composed of chips or may include chips and other discrete devices.

[0018] In a possible design, the chip system further includes a memory for storing necessary program instructions and data. The processor and the memory can be decoupled and separately disposed on different devices, connected by wired or wireless means, or the processor and the memory can also be coupled on the same device. Description of the Drawings

[0019] Figure 1 is a schematic flowchart of the steps of a method for surrounding environment target perception based on a millimeter-wave radar provided by the present application.

[0020] Figure 2 is a schematic diagram of obtaining a feedback signal provided by the present application.

[0021] Figure 3 is a schematic diagram of a method for obtaining true random numbers provided by the present application.

[0022] Figure 4 is a schematic diagram of a situation where intersections occur due to different slope adjustment methods provided by the present application.

[0023] Figure 5 is a schematic diagram of the principle of separating the main lobe in a spectrum provided by the present application.

[0024] Figure 6 is a schematic diagram of performing correlation processing on sidelobes with height variations provided by the present application. Detailed Description of the Embodiments

[0025] The following further elaborates on the technical solutions in the present application with reference to the accompanying drawings.

[0026] The present application discloses a method for surrounding environment target perception based on a millimeter-wave radar. Referring to Figure 1 , in some examples, the method for surrounding environment target perception based on a millimeter-wave radar disclosed in the present application includes the following steps: S101: Transmit a detection signal to the surrounding environment and obtain a feedback signal; S102: Analyze the feedback signal, determine the target perception objects included in the feedback signal, and continuously track the target perception objects; S103: Calculate the signal strength of the target perception objects. When the non-distance signal strength of the target perception object signal changes, calculate the sidelobe ratio in the feedback signal corresponding to the target perception object; S104: When the change intensity of the sidelobe ratio exceeds the allowable change range or the duration of the change intensity of the sidelobe ratio exceeds the set time, re-analyze other sidelobes in the feedback signal to determine whether there are hidden perception objects in the suppressed sidelobe signals.

[0027] Overall, the method for surrounding environment target perception based on millimeter-wave radar provided by this application aims to discover real targets in the surrounding environment. For example, when a target senses that it is being detected, it will take technical means to hide or create false targets for interference. At this time, appropriate technical means are needed to find the target and continuously track it.

[0028] In step S101, first, a detection signal is sent into the surrounding environment through a radar antenna and a feedback signal is obtained. As Figure 2 shown, Figure 2 the upper part above is the initial signal, and the lower part is the processed signal. This is a basic working process. Then, in step S102, the feedback signal is analyzed to determine the target perception objects included in the feedback signal and continuously track the target perception objects.

[0029] In this process, when the emitted electromagnetic wave signal encounters a target, part of its energy is reflected and received by the radar antenna. The received signal includes information such as the target's distance, speed, and azimuth. By processing the received signal, the position of the target perception object can be determined. Of course, signal processing is also required in this process, such as pulse compression, Doppler processing, constant false alarm rate processing, etc. This part of the content belongs to the prior art and will not be elaborated here.

[0030] To determine the position of the target perception object, three data of distance, speed, and angle are required. The relevant content is as follows: Distance measurement: Calculate the time difference Δt between the transmitted and received pulses. The distance R = c⋅Δt / 2 (c is the speed of light); Speed measurement: According to the Doppler frequency shift fd, the speed v = λfd / 2 (λ is the wavelength); Angle measurement: Determine the target azimuth through monopulse angle measurement (sum-difference beam amplitude comparison method) or phased array beam scanning.

[0031] In step S103, the signal strength of the target perception object is calculated. When the non-distance signal strength of the target perception object signal changes, calculate the sidelobe ratio in the feedback signal corresponding to the target perception object. Calculating the signal strength of the target perception object means calculating the energy corresponding to the main lobe part in the spectrum, and at the same time, it is required that the energy at this time is not caused by non-distance factors.

[0032] It should be understood that the feedback signal obtained in step S102 is a continuous signal. For the analysis method of such a continuous signal, a section of the signal is intercepted and then copied and extended to make it a continuous signal. In the process of signal interception, the problem of spectrum leakage will inevitably occur. The currently commonly used processing method is to use non-rectangular windows (such as Hanning window, Kaiser window), sacrificing resolution for leakage suppression, which can suppress the sidelobe to a certain extent.

[0033] The signal strength of the target perception object changes, mainly including distance changes, target attitude changes, and interference. Distance changes are normal phenomena, while target attitude changes and interference need to be processed. At this time, the sidelobe ratio in the feedback signal corresponding to the target perception object is calculated. The purpose of the calculation is in step S104. In step S104, according to the calculated result, the specific rules are as follows: When the change intensity of the sidelobe ratio exceeds the allowable change range or the duration of the change intensity of the sidelobe ratio exceeds the set time, re-analyze other sidelobes in the feedback signal to determine whether there are hidden perception objects in the suppressed sidelobe signals.

[0034] Here, two dimensions of change intensity and change intensity duration are given. When at least one of these two dimensions meets the conditions, the sidelobes in the feedback signal corresponding to the target perception object will be suppressed and re-analyzed, with the purpose of determining whether there are hidden perception objects in the suppressed sidelobe signals.

[0035] The change intensity and change intensity duration are specific set parameters that need to be set according to the specific environment and are not restricted here.

[0036] Specifically, the target attitude changes and interference mentioned above are technical means adopted by the target perception object to avoid being tracked. Target attitude changes generally mean a reduction in the reflection surface. At this time, the main lobe may be hidden in other sidelobes and cannot be detected. Interference generally means that the target perception object has taken active defense measures, such as adding false high-intensity signal targets, etc., which may also cause the main lobe to be hidden in other sidelobes and cannot be detected.

[0037] At this time, it is necessary to re-analyze other sidelobes in the feedback signal to determine whether there are hidden perception objects in the suppressed sidelobe signals.

[0038] In some possible implementation manners, algorithms such as trajectory tracking algorithms can be used to associate the front and rear breakpoints. However, this method associates through inference, and when the vacant time period between two breakpoints is long, there is a considerable difficulty in association.

[0039] Therefore, when the signal strength (non-distance factor) of the target perception object changes, targeted processing needs to be carried out immediately to discover whether there are hidden perception objects. Here, the hidden perception object refers to a newly emerging target perception object, such as an aircraft launched by a mother ship, or a target perception object hidden due to false signals.

[0040] In some examples, when continuously tracking a target perception object, the detection signal is adjusted using a dynamic slope method. The dynamic slope method for adjusting the detection signal includes slope adjustment and duration adjustment. The purpose of the dynamic slope adjustment method is to reduce the probability of being interfered with.

[0041] It should be understood that when the radar tracks a target, the specific process of the target countering by intercepting the radar signal is to disrupt the normal detection and tracking functions of the radar through interference or deception means. This process involves two steps: signal interception and parameter analysis, and interference signal synthesis. The core is to make the radar produce incorrect results by transmitting incorrect feedback signals.

[0042] Using the dynamic slope method to adjust the detection signal can make the detection signal in a dynamic change process. This method increases the processing time of signal interception and parameter analysis and interference signal synthesis. When these two steps are completed, the generated interference signal can no longer be used.

[0043] The dynamic slope method for adjusting the detection signal includes two aspects: slope adjustment and duration adjustment. At this time, true random numbers need to be used. Please refer to Figure 3 , and the acquisition method of true random numbers is as follows: Input at least one of the temperature parameter, environmental noise parameter, detection signal parameter (such as base noise value, signal-to-noise ratio value, energy peak, etc.) and feedback signal parameter (such as base noise value, signal-to-noise ratio value, energy peak, etc.) as basic data into the random number generator to generate a random number sequence, and select the slope adjustment parameter and duration adjustment parameter from the random number sequence. For example, in Figure 3 , select three digits as the slope adjustment parameter and duration adjustment parameter. The specific processing method is to accumulate until a single-digit or two-digit number is obtained. Of course, this is just an example. As long as it is obtained within the established rules, it can be used as the slope adjustment parameter and duration adjustment parameter.

[0044]

[0045] The dynamic slope here usually refers to the rate of change of at least one of the frequency, phase, or amplitude in the signal parameters over time.

[0046] In some examples, when using the dynamic slope method to adjust the detection signal, it also includes calculating the clutter signal energy ratio in the feedback signal and dynamically adjusting the slope adjustment parameter according to the clutter signal energy ratio. This method is to avoid the receiving intensity of the receiver exceeding the maximum allowable load.

[0047] ​It should be understood that for a receiver, it needs to receive all signals, among which there are feedback signals and clutter signals. Here, the clutter signals refer to the signals received by the receiver other than the feedback signals, and the clutter signals do not participate in the subsequent sidelobe signal analysis process.

[0048] The dynamic adjustment parameter of the slope adjustment parameter is related to the proportion of the clutter signal energy in the feedback signal. This is because the dynamic adjustment parameter has two types: positive parameter and negative parameter. At this time, whether to use a positive parameter or a negative parameter needs to be determined according to specific circumstances, and it is necessary to ensure that the receiving intensity of the receiver is less than the saturation receiving intensity.

[0049] The receiving intensity of the receiver is generally controlled below 0.8 - 0.9 times of the saturation receiving intensity. The reserved receiving intensity margin, on the one hand, is to avoid the continuous high-intensity operation of the receiver, and on the other hand, is to cope with emergencies. For example, when the signal suddenly strengthens, it can still have a certain processing ability.

[0050] In addition, for the antennas located in the same matrix, the same slope adjustment parameter and duration adjustment parameter need to be used. The purpose is to avoid mutual interference between the antennas in the same matrix, as Figure 4 shown. This is because if different slope adjustment methods are used, intersections will occur, and at this time, the feedback signals cannot be clearly distinguished, resulting in false targets.

[0051] Calculating the sidelobe ratio in the feedback signal corresponding to the target perception object refers to calculating the ratio of the energy corresponding to the sidelobe to the sum of the main lobe energy and the sidelobe energy. When In some examples, when calculating the sidelobe ratio in the feedback signal corresponding to the target perception object, the following content is also added: Inserting a random phase lag in the detection signal; Comparing the spectrum before the insertion of the random phase lag and the spectrum after the insertion of the random phase lag to determine the overlapping time between the peaks; Adjusting the random phase lag according to the overlapping time to make the overlapping time between the peaks tend to zero.

[0052] In the above content, the purpose of using the random phase lag is to separate the main lobe in the spectrum, as Figure 5 shown. This is because for the perception of the target perception object, if two target perception objects are simultaneously perceived at the same frequency, then on the spectrum of the obtained feedback signal, the main lobes at a certain point will overlap. Especially when the distance between the target perception objects is relatively close, at this time, it is necessary to insert a random phase lag in the detection signal to make the overlapping time between the peaks tend to zero, that is, to separate the two peaks.

[0053] Of course, when inserting a random phase lag into the detection signal, it is also necessary to divide the coverage area of the detection signal. The random phase lag of the detection signal pairs corresponding to each area is different, with the aim of enabling the peaks in the obtained spectrum to be separated.

[0054] In some examples, the specific method for suppressing the sidelobes in the feedback signal corresponding to the target perception object is as follows: Select two detection signals in the time series, and insert a random phase lag into at least one of the two detection signals; Determine the sidelobes with significant height variations; Perform correlation processing on the sidelobes with significant height variations; Determine whether there is a hidden perception object based on the result of the correlation processing.

[0055] In the above method, first, it is necessary to select two detection signals in the time series, and insert a random phase lag into at least one of the two detection signals, with the aim of determining the sidelobes with significant height variations. During the comparison process here, it is allowed for one of the detection signals to move in the time dimension to cancel out the inserted random phase lag.

[0056] Next, determine the sidelobes with significant height variations, and then perform correlation processing on the sidelobes with significant height variations. The method of correlation processing is to determine the main lobe and the sidelobes through symmetry. The height of the main lobe is greater than that of the sidelobes. The sidelobes are symmetric on both sides of the main lobe, and the height of the sidelobes decreases successively in the direction away from the main lobe, as Figure 6 shown.

[0057] If the main lobe and the sidelobes meeting the above requirements exist after the correlation processing, it indicates the existence of a hidden perception object; otherwise, it indicates the non-existence of a hidden perception object.

[0058] In some examples, the specific steps for performing correlation processing on the sidelobes with significant height variations are as follows: Determine the height variation value of the sidelobes with significant height variations; Perform correlation processing on the sidelobes with significant height variations according to the height variation value. During the correlation processing, each height variation value can be used as the height of the main lobe.

[0059] In some examples, after obtaining the hidden perception object, the following additional operations are performed: Continuously track the existing hidden perception object in the time series; Determine the existence time of the existing hidden perception object in the time series; Perform retention processing and deletion processing on the hidden perception object according to the existence time.

[0060] The purpose of this method is to determine whether the obtained hidden perception object is real. This is because in the processing method described above, the hidden perception object is obtained through an inference method, and there are certain misjudgments in the inference method, which are affected by the obtained data and the processing process, and its accuracy cannot be completely accurate. Therefore, a verification step needs to be added.

[0061] Verification means that during multiple processing processes, if the obtained hidden perception objects all exist, then this hidden perception object is retained, otherwise it is deleted. Generally speaking, the number of processing times corresponding to the existence time is 3 - 5 times. Here, it is required that during multiple processes of the hidden perception object, the error of the main lobe height is within 3% - 5%, and the side lobes meet the requirements that the side lobes are symmetric on both sides of the main lobe and the height of the side lobes decreases successively in the direction away from the main lobe.

[0062] This application also provides a surrounding environment target perception device based on a millimeter - wave radar, including: A signal transceiver unit, which is used to send detection signals to the surrounding environment and obtain feedback signals; A signal processing unit, which is used to analyze the feedback signals, determine the target perception objects included in the feedback signals, and continuously track the target perception objects; A signal calculation unit, which is used to calculate the signal intensity of the target perception objects. When the non - distance signal intensity of the target perception object signal changes, calculate the side - lobe ratio in the corresponding feedback signal of the target perception object; A signal re - processing unit, which is used to re - analyze other side lobes in the feedback signals when the change intensity of the side - lobe ratio exceeds the allowable change range or the duration of the change intensity of the side - lobe ratio exceeds the set time, and determine whether there are hidden perception objects in the side - lobe signals after suppression.

[0063] Furthermore, when continuously tracking the target perception objects, the detection signals are adjusted using the dynamic slope method. The dynamic slope method for adjusting the detection signals includes slope adjustment and duration adjustment; When using the dynamic slope method to adjust the detection signals, at least one of the temperature parameter, the environmental noise parameter, the detection signal parameter, and the feedback signal parameter is used as basic data to be input into a random number generator to generate a random number sequence, and the slope adjustment parameter and the duration adjustment parameter are selected from the random number sequence.

[0064] Furthermore, when using the dynamic slope method to adjust the detection signals, it also includes calculating the clutter signal energy ratio in the feedback signals and dynamically adjusting the slope adjustment parameter according to the clutter signal energy ratio; The dynamic adjustment parameter of the slope adjustment parameter is related to the clutter signal energy ratio in the feedback signals; When dynamically adjusting the slope adjustment parameter, the received strength of the receiver is less than the saturation received strength; Antennas located in the same matrix use the same slope adjustment parameter and duration adjustment parameter.

[0065] Further, when calculating the sidelobe ratio in the feedback signal corresponding to the target sensing object, it further includes: Insert a random phase lag in the detection signal; Compare the spectrum before the insertion of the random phase lag and the spectrum after the insertion of the random phase lag, and determine the overlapping time between the peaks; Adjust the random phase lag according to the overlapping time to make the overlapping time between the peaks tend to zero.

[0066] Further, the re - analysis of other sidelobes in the feedback signal includes: Select two detection signals in the time series, and insert a random phase lag into at least one of the two detection signals; Determine the sidelobes with height changes; Perform correlation processing on the sidelobes with height changes; Determine whether there is a hidden sensing object according to the result of the correlation processing.

[0067] Further, the correlation processing of the sidelobes with height changes includes: Determine the height change value of the sidelobes with height changes; Perform correlation processing on the sidelobes with height changes according to the height change value. During the correlation processing, each height change value can be used as the main lobe height.

[0068] Further, after obtaining the hidden sensing object, it further includes: Continuously track the existing hidden sensing object in the time series; Determine the existence time of the existing hidden sensing object in the time series; Perform retention processing and deletion processing on the hidden sensing object according to the existence time.

[0069] In one example, the units in any of the above devices can be one or more integrated circuits configured to implement the above - mentioned method. For example: one or more application specific integrated circuits (ASICs), or, one or more digital signal processors (DSPs), or, one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0070] For another example, when the units in the device can be implemented in the form of a processing element scheduler, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call programs. For another example, these units can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0071] In this application, names are given to various objects such as various messages / information / devices / network elements / systems / devices / actions / operations / processes / concepts, etc. that may appear. It can be understood that these specific names do not constitute limitations on the relevant objects, and the given names can be changed according to factors such as scenarios, contexts, or usage habits. The understanding of the technical meanings of the technical terms in this application should be mainly determined from the functions and technical effects reflected / executed in the technical solutions.

[0072] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0073] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0074] 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 can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0075] Those of ordinary skill in the art will realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0076] It should also be understood that in various embodiments of this application, the first, second, etc. are only used to indicate that multiple objects are different. For example, the first time window and the second time window are only used to indicate different time windows. And it should not have any impact on the time window itself. The above first, second, etc. should not impose any restrictions on the embodiments of this application.

[0077] It should also be understood that in various embodiments of this application, if there is no special indication of logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other. The technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0078] If the described functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. And the aforementioned computer-readable storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0079] This application also provides a surrounding environment target perception system based on a millimeter-wave radar. The system includes: One or more memories for storing instructions; One or more processors for calling and running the instructions from the memory and executing the methods described above.

[0080] This application also provides a computer program product. The computer program product includes instructions that, when executed, cause the terminal device and the network device to perform the operations of the terminal device and the network device corresponding to the above methods.

[0081] The present application also provides a chip system, which includes a processor for implementing the functions involved in the above content. For example, generating, receiving, sending, or processing the data and / or information involved in the above method.

[0082] The chip system can be composed of chips or can include chips and other discrete devices.

[0083] The processor mentioned anywhere above can be a CPU, a microprocessor, an ASIC, or an integrated circuit for executing one or more programs for controlling the transmission of the above feedback information.

[0084] In a possible design, the chip system further includes a memory for storing necessary program instructions and data. The processor and the memory can be decoupled and disposed on different devices and connected by wired or wireless means to support the chip system in implementing various functions in the above embodiments. Alternatively, the processor and the memory can also be coupled on the same device.

[0085] Optionally, the computer instructions are stored in the memory.

[0086] Optionally, the memory is a storage unit within the chip, such as a register, a cache, etc. The memory can also be a storage unit outside the chip within the terminal, such as a ROM or other types of static storage devices that can store static information and instructions, a RAM, etc.

[0087] It can be understood that the memory in the present application can be a volatile memory or a non-volatile memory, or can include both a volatile memory and a non-volatile memory.

[0088] The non-volatile memory can be a ROM, a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), or a flash memory.

[0089] The volatile memory can be a RAM, which is used as an external cache. There are various different types of RAM, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synch link DRAM (SLDRAM), and direct rambus random access memory.

[0090] The embodiments of the specific implementation manners are all preferred embodiments of the present application, and do not limit the protection scope of the present application. Therefore, all equivalent changes made according to the structure, shape, and principle of the present application shall be covered within the protection scope of the present application.

Claims

1. A method for surrounding environment target perception based on millimeter-wave radar, characterized in that include: Send detection signals to the surrounding environment and get feedback signals; Analyzing the feedback signal, determining the target perception object included in the feedback signal, and continuously tracking the target perception object; Calculating the signal strength of the target perception object, and when the non-range signal strength of the target perception object signal changes, calculating the sidelobe ratio in the feedback signal corresponding to the target perception object; When the change intensity of the sidelobe ratio exceeds the allowable change range or the duration of the change intensity of the sidelobe ratio exceeds the set time, the other sidelobes in the feedback signal are re-analyzed to determine whether there is a hidden perception object in the suppressed sidelobe signal.

2. The method for surrounding environment target perception based on millimeter-wave radar according to claim 1, wherein When continuously tracking a target perception object, a dynamic slope method is used to adjust the detection signal. The dynamic slope method includes slope adjustment and duration adjustment. When the dynamic slope method is used to adjust the detection signal, at least one of the temperature parameter, the environmental noise parameter, the detection signal parameter and the feedback signal parameter is input as basic data into a random number generator to generate a random number sequence, and the slope adjustment parameter and the duration adjustment parameter are selected from the random number sequence.

3. The method for surrounding environment target perception based on millimeter-wave radar according to claim 2, wherein When the dynamic slope method is used to adjust the detection signal, it also includes calculating the energy ratio of the clutter signal in the feedback signal and dynamically adjusting the slope adjustment parameter according to the energy ratio of the clutter signal; The dynamic adjustment parameter of the slope adjustment parameter is related to the proportion of the clutter signal energy in the feedback signal; When the slope adjustment parameter is dynamically adjusted, the receiving intensity of the receiver is less than the saturation receiving intensity; Antennas in the same matrix use the same slope adjustment parameter and duration adjustment parameter.

4. The method for perceiving surrounding environment targets based on millimeter-wave radar according to claim 1, characterized in that, When calculating the sidelobe ratio in the feedback signal corresponding to the target perception object, the method further includes: Inserting random phase lag into the detection signal; Comparing the spectrum before and after the random phase lag insertion to determine the overlap time between the peaks; The random phase lag is adjusted according to the overlap time so that the overlap time between peaks approaches zero.

5. The method for surrounding environment target perception based on millimeter-wave radar according to claim 4, wherein Reanalysis of other sidelobes in the feedback signal includes: Two detection signals are selected in the time series, and a random phase lag is inserted into at least one of the two detection signals; Determine the presence of highly varying sidelobes; Perform correlation processing on side lobes with high variations; Determine whether there is a hidden perception object based on the association processing result.

6. The method for perceiving surrounding environment targets based on millimeter-wave radar according to claim 5, characterized in that, Correlation processing of highly varying sidelobes includes: Determining a height variation value of a side lobe having a height variation; The side lobes with height changes are subjected to association processing according to the height change values. During the association processing, each height change value can be used as the main lobe height.

7. The method for surrounding environment target perception based on millimeter wave radar according to claim 6, characterized in that, When determining the presence of hidden perception objects, it also includes: Continuously track the existence of hidden perception objects in time series; Determine the existence time of the hidden perceptual object in the time series; Hidden-aware objects are retained or deleted according to their existence time.

8. A surrounding environment target perception device based on a millimeter-wave radar, which adopts the method described in any one of claims 1 to 7, characterized in that, include: A signal transceiver unit is used to send a detection signal to the surrounding environment and obtain a feedback signal; A signal processing unit, configured to analyze the feedback signal, determine the target perception object included in the feedback signal, and continuously track the target perception object; A signal calculation unit is used to calculate the signal strength of the target perception object, and when the non-range signal strength of the target perception object signal changes, calculate the sidelobe ratio in the feedback signal corresponding to the target perception object; The signal reprocessing unit is used to reanalyze other sidelobes in the feedback signal when the intensity of the change in the sidelobe ratio exceeds the allowable change range or the duration of the change in the sidelobe ratio exceeds the set time, so as to determine whether there is a hidden perceptual object in the suppressed sidelobe signal.

9. A millimeter-wave radar-based ambient target perception system, characterized in that: The system comprises: one or more memories for storing instructions; One or more processors, configured to call and execute the instructions from the memory to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program, and when the program is executed by a processor, the method according to any one of claims 1 to 7 is performed.

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