Signal processing method and apparatus, radar, circuit, sensor, terminal, and medium

Abstract

A signal processing method and apparatus, a radar, a circuit, a sensor, a terminal, and a medium. The signal processing method comprises: on the basis of an initial count of targets in the direction of arrival of an echo signal, estimating position information and amplitude of each target under a current target count; calculating a current energy residual on the basis of the position information and amplitude of the target; and if the energy residual is greater than a preset threshold, increasing the current target count, re-estimating the position information and amplitude of each target under the current target count until the current energy residual is smaller than the preset threshold, wherein in estimating the position information and amplitude of the target, the position information and amplitude of the target are obtained by performing FFT processing and Chirp Z transformation processing on a target signal.

Description

Signal processing method and device, radar, circuit, sensor, terminal and medium

[0001] The present application claims priority from the Chinese patent application No. 202410686835.0 filed on May 29, 2024 and entitled "A signal processing method, device, radar, terminal and medium", the contents of which should be understood as incorporated herein by reference. TECHNICAL FIELD

[0002] The present document relates to, but is not limited to, the technical field of radar, in particular to a signal processing method, device, radar, circuit, sensor, terminal and medium. BACKGROUND

[0003] With the development of 4D cascaded imaging radar technology, higher requirements are put forward for the angle accuracy and angle resolution of millimeter wave radar. In order to obtain the contour point cloud of the target, the DOA (Direction Of Arrival) needs to achieve higher angle resolution and more angle resolution numbers; at the same time, the point cloud number of 4D imaging radar is larger, and the DOA algorithm needs to have good real-time performance. The determination of the direction of arrival of the signal needs to rely on the number of signal sources, and if the signal source data is estimated incorrectly, the angle resolution will be affected. SUMMARY

[0004] The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

[0005] In one aspect, the embodiments of the present disclosure provide a signal processing method, comprising:

[0006] Based on the initial target number of the direction of arrival of the echo signal, the position information and the amplitude of each target under the current target number are estimated, the current energy residual is calculated according to the position information and the amplitude of the target, if the energy residual is greater than a preset threshold value, the current target number is increased, the position information and the amplitude of each target under the current target number are re-estimated, until the current energy residual is less than the preset threshold value, wherein when the position information and the amplitude of the target are estimated, the position information and the amplitude of the target are obtained by performing FFT processing and Chirp Z transform processing on the target signal.

[0007] In another aspect, the embodiments of the present disclosure also provide a signal processing device, comprising a processor and a memory storing a computer program executable on the processor, wherein the processor implements the steps of the signal processing method as described above when executing the program.

[0008] In another aspect, embodiments of this disclosure also provide a radar, the radar including a transceiver and a processor, the transceiver including: at least one antenna, wherein: the transceiver is used to transmit a detection signal and to receive an echo signal reflected by the detection signal from a target; the processor is used to execute the signal processing method as described above.

[0009] In another aspect, embodiments of this disclosure also provide an integrated circuit, including a signal transceiver and a processor, wherein: the signal transceiver is used to transmit a detection signal and to receive an echo signal reflected by the detection signal from a target; the processor is used to process the echo signal using the aforementioned signal processing method to achieve target detection.

[0010] In another aspect, embodiments of this disclosure also provide an electromagnetic wave sensor, including: a carrier, an integrated circuit as described above, and an antenna, wherein the integrated circuit is disposed on the carrier; the antenna is disposed on the carrier, or the antenna and the integrated circuit are integrated into a single device disposed on the carrier; wherein the integrated circuit is connected to the antenna and is used to transmit electromagnetic wave signals and / or receive echo signals.

[0011] In another aspect, embodiments of this disclosure also provide a terminal, which includes the aforementioned radar, integrated circuit, or electromagnetic wave sensor.

[0012] In another aspect, embodiments of this disclosure also provide a computer-readable storage medium storing computer-executable instructions for performing the signal processing method as described above.

[0013] After reading and understanding the accompanying diagrams and detailed descriptions, the other aspects can be understood.

[0014] Overview of the attached figures

[0015] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0016] Figure 1 is a flowchart of an embodiment of this disclosure;

[0017] Figure 2 is a flowchart of signal processing according to an embodiment of this disclosure;

[0018] Figure 3 is a schematic diagram of the ULA signal.

[0019] Figure 4 is a flowchart of the chirp Z-transform;

[0020] Figure 5A shows the FFT result of the original signal x0;

[0021] Figure 5B shows the CZT results of the original signal x0;

[0022] Figure 6A shows the source number resolution results using the DBF method;

[0023] Figure 6B shows the source number resolution results using the DML method;

[0024] Figure 6C is a diagram showing the source number resolution results using the Relax method in an embodiment of this disclosure;

[0025] Figure 7 is a comparison of RMSE (root mean square error) for different algorithms;

[0026] Figure 8 is a schematic diagram of a signal processing device according to an embodiment of the present disclosure;

[0027] Figure 9 is a schematic diagram of a radar according to an embodiment of this disclosure;

[0028] Figure 10 is a schematic diagram of an integrated circuit according to an embodiment of this disclosure;

[0029] Figure 11 is a schematic diagram of an electromagnetic wave sensor according to an embodiment of this disclosure;

[0030] Figure 12 is a schematic diagram of a terminal device according to an embodiment of this disclosure.

[0031] Detailed Explanation

[0032] This application describes several embodiments, but these descriptions are exemplary and not limiting, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in detail, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0033] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application can also be combined with any conventional features or elements to form unique inventive solutions. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application can be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes can be made within the scope of the appended claims.

[0034] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0035] In the field of radar, radar sends a detection signal to a target, and the target reflects an echo signal back to the radar. The radar processes the echo signal reflected from the target to determine the target's distance, speed, and angle, thereby achieving target localization. The radar can also be called a radar transceiver. This localization method can be applied to fields such as autonomous driving, security, and drones. For example, after receiving the echo signal, the radar first performs analog-to-digital conversion (AD) on the echo signal, then samples the resulting digital signal, and sequentially performs one-dimensional fast Fourier transform (1DFFT) and two-dimensional fast Fourier transform (2DFFT) on the sampled digital signal to accumulate the echo signal and obtain the target's Doppler frequency. Then, it performs constant false alarm rate (CFAR) detection to distinguish the echo signal from noise, thus determining whether the target signal exists. This identifies targets with the same distance and speed. Further processing of these targets with the same distance and speed yields the number of target objects, i.e., the number of signal sources, which is used for subsequent calculation of the direction of arrival (or direction of arrival, i.e., the target's angle).

[0036] In existing 4D imaging DOA (Directivity of Alignment), the traditional DBF (Digital Beamforming) method is simple to implement and can achieve multi-target resolution under single-shot conditions. However, its resolution is not high, and its dynamic range is low due to its high sidelobe level. The Capon (Minimum Variance Unbiased Estimation) / MUSIC (Multiple Signal Classification) algorithm can achieve good resolution and dynamic range, but its performance is significantly reduced under single-shot conditions. Moreover, with a large number of 4D imaging channels, its real-time performance is poor, from design to matrix inversion and matrix eigenvalue decomposition. The ESPRIT (Extended Subspace Minimal Squares) algorithm can achieve good resolution and dynamic range through spatial smoothing, but it requires a uniform linear antenna array, which imposes significant constraints on antenna design. The DML (Deterministic Maximum Likelihood) algorithm can achieve good resolution and dynamic range and is also applicable under single-shot conditions, but its computational complexity increases exponentially when the number of signal sources is greater than 2, resulting in poor real-time performance.

[0037] Therefore, this disclosure provides a signal processing method, as shown in FIG1, including:

[0038] Based on the initial number of targets in the direction of arrival of the echo signal, the position information and amplitude of each target under the current number of targets are estimated. The current energy residual is calculated based on the position information and amplitude of the targets. If the energy residual is greater than a preset threshold, the current number of targets is increased, and the position information and amplitude of each target under the current number of targets are re-estimated until the current energy residual is less than the preset threshold. In estimating the position information and amplitude of the targets, the position information and amplitude of the targets are obtained by performing FFT processing and Chirp Z-transform processing on the target signals.

[0039] This disclosure embodiment estimates the target's position and amplitude using energy residuals, reducing computational load. Furthermore, the combination of FFT processing and chirp-Z transform refines the spectrum, improving the accuracy of target position and amplitude estimation and enhancing robustness. In summary, the signal processing method of this disclosure embodiment improves signal processing performance.

[0040] The aforementioned location information includes: angle or distance frequency or Doppler frequency.

[0041] In an exemplary embodiment, before estimating the position information of each target with the current number of targets, the method further includes obtaining the echo signal of a uniform linear array (ULA) by zero-padding the positions without signal. By processing the echo signal into ULA form, the sidelobes of the signal after subsequent FFT processing can be reduced, and the convergence speed and accuracy of subsequent calculations can be improved.

[0042] In an exemplary embodiment, the above-mentioned method of increasing the current number of targets and re-estimating the position information and amplitude of each target under the current number of targets includes: incrementing the current number of targets by 1; using the previously estimated position information and amplitude of each target to calculate the remaining signal in the echo signal as the signal of the newly added target; and obtaining the position information and amplitude of the newly added target by performing FFT processing and Chirp Z-transform processing on the signal of the newly added target. By estimating the angle and amplitude of each target by gradually increasing the number of targets, the computational complexity can be reduced and the accuracy of position information estimation can be improved.

[0043] In an exemplary embodiment, after obtaining the position information and amplitude of the newly added target by performing FFT and Chirp Z-transform processing on the remaining signal, the method further includes repeating the following steps until the target position information converges: For each target, with the position information and amplitude of other targets fixed, the remaining signal in the echo signal is calculated based on the position information and amplitude of other targets as the signal of the current target; the current target signal is then subjected to FFT and Chirp Z-transform processing to obtain the new position information and amplitude of the current target. By calculating the position information and amplitude of each target using the above iterative optimization method, the mutual influence between targets can be eliminated, achieving complete separation between targets. Furthermore, it can reduce the computational load and complexity of simultaneously calculating all targets. The calculation process in the above embodiment utilizes a relaxation algorithm, performing multi-target discrimination through repeated iterative calculations, which can achieve better signal processing performance.

[0044] For example, when the preset number of targets is 1, obtaining the position information and amplitude of the target by performing FFT processing and Chirp Z-transform processing on the target signal includes:

[0045] Perform FFT processing on the target signal to obtain the first frequency corresponding to the energy with the largest spectrum;

[0046] A first frequency range is set according to the first frequency (for example, the first frequency ± 1 / L, where L is the number of discrete data points processed by the FFT). The target signal is subjected to Chirp Z-transform processing according to the first frequency range to obtain the second frequency and the corresponding amplitude corresponding to the energy with the largest spectrum. The amplitude is used as the amplitude of the current target.

[0047] The position information of the target signal is obtained based on the second frequency and amplitude.

[0048] For example, when the preset number of targets is 2, the step of obtaining the position information and amplitude of the targets by performing FFT processing and Chirp Z-transform processing on the target signals includes:

[0049] The position information and amplitude calculated when the number of preset targets is 1 are used as the position information and amplitude of the first target. The remaining signal in the echo signal is calculated using the position information and amplitude of the first target and used as the signal of the second target. The signal of the second target is processed by FFT to obtain the third frequency corresponding to the energy with the largest spectrum.

[0050] A second frequency range is set according to the third frequency (e.g., the third frequency ± 1 / L), and the target signal is subjected to Chirp Z-transform processing according to the second frequency range to obtain the fourth frequency and the corresponding amplitude corresponding to the energy with the largest spectrum. The amplitude is used as the amplitude of the second target.

[0051] The position information of the second target is obtained based on the fourth frequency and amplitude.

[0052] In an exemplary embodiment, after increasing the current target number, the method may further include terminating the current signal processing flow if the current target number reaches a preset maximum target number.

[0053] The method for estimating the number of signal sources provided in this embodiment will be described in detail below, and the process is shown in Figure 2.

[0054] Step 1, Signal Sampling; Assume K far-field signals are incident on an antenna containing M elements, and the set of incident angles of the K signals is... The received signal of the array can then be written as:

[0055] Where x represents the signal vector, s i Let A(θ) be the signal vector of the i-th source. iLet be the steering vector of the i-th source, and n be the noise. The signal vector refers to the representation of the signal received by the radar in the complex domain, including the signal's amplitude and phase information. The source signal vector refers to the vector form of the signal data collected from the source, organized according to certain rules. The source steering vector is used to describe the steering properties of a signal originating from a specific direction or angle; this vector is typically used to indicate the signal's incident angle or radiation direction.

[0056] Step 2, calculate the signal energy, P x =x H x, where x H This represents the conjugate transpose of x;

[0057] Step 3: Assuming the number of targets is 1, estimate the magnitude of the target. and angle Wherein, the subscript represents the target number, the superscript represents the total number of targets currently assumed, and the energy residual is calculated;

[0058] Step 3 includes:

[0059] Step 3.1, fill the signal x with zeros (fill the position where there is no signal with zeros) to obtain the ULA signal x, as shown in Figure 3. In the figure, the circular position represents the virtual channel after array MIMO, and the square position represents the supplementary unit to supplement the array into an equally spaced array.

[0060] Padding the signal with zeros to obtain the ULA signal can result in low sidelobes in the signal after subsequent FFT processing, and can improve the convergence speed and accuracy of subsequent calculations.

[0061] Step 3.2: Coarsely sample (or coarsely search) the zero-padded signal. In this example, coarse sampling is performed using FFT, where the number of FFT points is set to L, resulting in the FFT spectrum. The frequency f1 corresponding to the maximum energy;

[0062] Since the number of targets is set to 1 in step 3, only the frequency corresponding to the maximum energy needs to be obtained. Through FFT processing, the frequency corresponding to the maximum energy in the FFT spectrum is obtained, thus determining a coarse search range, i.e., the first frequency range.

[0063] The number of points in an FFT refers to the number of discrete data points in the input signal during the FFT process. This number of points determines the spectral resolution and accuracy of the FFT output. During FFT analysis, the input signal is divided into L discrete data points, where L is a positive integer. Common point numbers include 8, 16, 32, 64, 128, 256, etc. Choosing different point numbers affects the FFT's computation speed and spectral resolution. A higher number of points provides higher spectral resolution but also requires more computational resources.

[0064] Step 3.3: Perform fine sampling (or fine search) on the coarsely sampled signal within the first frequency range. The fine spectrum of x is obtained by performing a Chirp Z-transform on x. Where L is used to determine the fine sampling range, and 1 / L represents the frequency after the FFT transformation;

[0065] The Chirp Z-Transform (CZT) captures the frequency characteristics of a signal as it changes over time by converting a time-series signal into a frequency-time-frequency representation. One method for Chirp Z-Transform includes: generating a Chirp signal, determining the sampling frequency, and selecting the number of discrete data points to be transformed; sampling the Chirp signal in the time domain to obtain a discrete time series; multiplying the time-domain sampled sequence by a Chirp harmonic function to increase frequency resolution; and performing an FFT on the signal multiplied by the harmonic function to obtain the Chirp Z-transformed spectrum. To efficiently implement the Chirp Z-Transform, FFT and IFFT algorithms can be used to accelerate the frequency domain conversion and inverse conversion process. As shown in Figure 4, the signal is processed by FFT to obtain a representation in the frequency domain, and then the calculated frequency domain data is converted back to the time domain by IFFT. By utilizing the efficient properties of FFT and IFFT, the computational complexity and speed of Chirp Z-Transform calculation can be reduced.

[0066] Figure 5A is a schematic diagram of the coarse search result using FFT processing, and Figure 5B is a comparison diagram of the coarse search result after fine search using Chirp Z-transform processing. In Figure 5B, the solid line is the FFT result, and the dotted solid line is the Chirp Z-transform result. It can be seen that the Chirp Z-transform result is more detailed and smoother.

[0067] Step 3.4, based on this refined spectrum This fine spectrum can be obtained. Maximum energy frequency (i.e., the frequency corresponding to the maximum energy in the spectrum) and the amplitude of the corresponding signal. The target angle estimate is calculated using the following formula. And the energy residual, i.e., the residual energy R1, where:

[0068] Step 3.5: If the residual R1 is greater than the preset first threshold Th1, it is considered that there is still a target in the remaining energy, and more targets are identified. The number of targets is incremented by 1, and step 4 is executed. Otherwise, the signal processing flow is terminated.

[0069] For example, the first threshold Th1 can be determined based on the ratio of the current energy to the total energy, such as based on the energy calculated in step 3.4. P, representing the total signal energy in step 2 x The ratio is determined. R1 / P can be used for comparison. x Compare with Th1.

[0070] Step 4: Assuming there are 2 targets, estimate the magnitude of each target. and angle Wherein, the subscript represents the target number, the superscript represents the total number of targets currently assumed, and also represents the iteration number (the second iteration in this step), as well as the calculation of the energy residual;

[0071] Step 4 includes:

[0072] Step 4.1, initialize the angle of target 1 as the result of step 3.

[0073] Step 4.2: Calculate the remaining signal based on the current target's amplitude and angle. The remaining signal refers to the portion of the signal remaining after removing the target 1 signal from the currently received signal;

[0074] Step 4.3, for the signal Perform FFT and Chirp Z-transform (processing steps 3.2–3.4) to obtain the initial estimate of target 2. and amplitude

[0075] Since the angle and magnitude of target 1 have already been estimated in step 3, this step only needs to obtain the angle and magnitude of target 2 through FFT processing and Chirp Z-transform processing.

[0076] Step 4.4: Using the angle and amplitude of target 2 estimated in step 4.3, re-estimate the angle and amplitude of target 1: calculate the signal of target 1. For signals Perform FFT processing and Chirp Z-transform (processing steps 3.2–3.4) to obtain an estimate of target 1. and amplitude

[0077] Step 4.5: Repeat steps 4.2 to 4.4 until convergence, i.e., the angles of target 1 and target 2 no longer change, and obtain...

[0078] By calculating the angle and magnitude of only one target at a time, and then iteratively calculating the final angle and magnitude of each target, the computational complexity and computational load are reduced.

[0079] Step 4.6, calculate the residual energy, i.e., the energy residual R2:

[0080] Step 4.7: If the residual energy R2 is greater than the preset second threshold Th2, it is considered that there is still a target in the residual energy, and more targets are identified. The number of targets is incremented by 1, and step 5 is executed. Otherwise, the signal processing flow is terminated.

[0081] Step 5: Assuming the number of targets is K, estimate the magnitude of the targets. and angle And calculate the energy residual;

[0082] Step 5 includes:

[0083] Step 5.1: Based on the test results from the previous step, initialize... The remaining signal is calculated using the following formula:

[0084] Step 5.2, for the signal Perform FFT processing and Chirp Z-transform to obtain an initial estimate of the target K. and amplitude

[0085] Step 5.3: Obtain the signal of the m-th target sequentially. The obtained signal is processed by FFT and Chirp Z-transform to obtain an estimate of the target m. and amplitude

[0086] Taking three targets as an example, since the angles and amplitudes of two targets have already been obtained in step 4, the remaining signal obtained by subtracting the signals of the first and second targets from the echo signal using the formula in step 5.1 is used as the signal of the third target. The angle and amplitude of the third target are obtained by performing FFT and Chirp Z-transform on the signal of the third target. The angle and amplitude of the first target are then recalculated using the angle and amplitude of the third target and the angle and amplitude of the second target. The angle and amplitude of the second target are then recalculated using the angle and amplitude of the first target and the angle and amplitude of the third target. Through multiple iterations, convergence is considered to occur when the angles of the three targets no longer change or the change in amplitude is less than a preset value.

[0087] Step 5.4: Repeat step 5.3 iteratively until convergence;

[0088] Step 5.5, calculate the residual energy R K :

[0089] Steps 5 and 6: Determine if the residual R K If the value is greater than the preset threshold ThK, it is assumed that there are still targets in the remaining energy, the target number is incremented by 1, and more targets are identified; otherwise, the signal processing flow is terminated.

[0090] Step 6: Pre-set the maximum number of target resolutions K. max When K reaches its maximum value, max The process will terminate at that time.

[0091] For example, in steps 3.5, 4.7, and 5.6 above, after incrementing the target number by 1, it can be determined whether the current target number K has been reached. max If yes, the process terminates; otherwise, the subsequent steps are executed.

[0092] This embodiment employs a Relax algorithm for multi-target discrimination. This method eliminates mutual interference between targets through iterative optimization, achieving complete separation and thus target discrimination. Considering that performance loss is significant if there are deviations in the estimation of target amplitude and angle (due to sparse angle grid points), a chirp Z-transform is used to refine the spectrum. This enables robust multi-target (>2) discrimination in a single snapshot. Simultaneously, the characteristics of the chirp Z-transform simplify computational complexity, ensuring real-time processing requirements and achieving better robustness while accurately estimating target amplitude and angle. The number of target sources is ultimately estimated through residual energy estimation.

[0093] Assuming the angles of the two targets are [-1.5°, 1.5°] and the SNR (Signal-to-Noise Ratio) are [10dB, 10dB], 100 experiments are conducted. The number of steering vectors using the DBF method and the DML method is 512. In this example, the FFT size of the Relax algorithm is 64, and the number of Chirp Z-transform points is 64.

[0094] Figure 6A shows the statistical results of source number resolution using the DBF method, Figure 6B shows the statistical results of source number resolution using the DML method, and Figure 6C shows the statistical results of source number resolution using the Relax method according to the embodiments of this disclosure. As can be seen from Figures 6A to 6C, the DBF method may fail to resolve targets in high-resolution scenes, while both the Relax and DML algorithms can achieve accurate target resolution. Figure 7 shows the measurement variance for two targets with SNRs of [5, 10, 15, 20] dB. It is evident that the measurement variance of the Relax algorithm is lower than that of the DML algorithm; therefore, the Relax algorithm outperforms the DML algorithm.

[0095] Table 1 compares the computational costs of the algorithms (taking the Relax algorithm with 10 iterations as an example).

[0096] Table 1 Comparison of computational complexity

[0097] It is evident that the Relax algorithm has a moderate computational load and achieves the best performance among the three algorithms.

[0098] This disclosed embodiment can be used not only for DOA estimation, but also for the estimation of range frequency and Doppler frequency (for calculating velocity). The method and steps are the same as those in the previous embodiment. The difference is that, in step 1, when sampling the signal, the antenna dimension is not sampled. If range frequency estimation is to be performed, sampling is performed within the pulse. If Doppler frequency estimation is to be performed, sampling is performed between pulses.

[0099] This disclosure also provides a signal processing apparatus, as shown in FIG8. The signal processing apparatus includes a processor and a memory storing a computer program that can run on the processor, wherein the processor can implement the aforementioned signal processing method when executing the program.

[0100] This disclosure also provides a radar, as shown in FIG9. The radar includes a transceiver and a processor. The transceiver includes at least one antenna, wherein: the transceiver is used to transmit a detection signal and to receive an echo signal reflected by the detection signal from a target; the processor is used to execute the aforementioned signal processing method.

[0101] This disclosure also provides an integrated circuit, as shown in FIG10, including a signal transceiver and a processor, wherein: the signal transceiver is used to transmit a detection signal and to receive an echo signal reflected by the detection signal from a target; the processor is used to execute the signal processing method described in any of the foregoing embodiments to process the echo signal to achieve target detection.

[0102] For example, the processor may be a baseband (BB) unit and / or an MCU unit.

[0103] For example, the integrated circuit may be a millimeter-wave radar chip or a sensor chip.

[0104] In an exemplary embodiment, the integrated circuit may include a radio frequency (RF) module, an analog signal processing module, and a digital signal processing module connected in sequence; the RF module is used to generate an RF transmission signal and receive an echo signal; the analog signal processing module is used to down-convert the echo signal to obtain an intermediate frequency (IF) signal; the digital processing module is used to perform analog-to-digital conversion on the IF signal to obtain a digital signal; and the digital signal is processed based on the signal processing method in the embodiments of this disclosure to achieve target detection.

[0105] In some optional embodiments, the integrated circuit may be an AiP (Antenna-In-Package) chip structure, an AoP (Antenna-On-Package) chip structure, or an AoC (Antenna-On-Chip) chip structure.

[0106] According to some other embodiments of this disclosure, an electromagnetic wave sensor is also proposed. This electromagnetic wave sensor may include an antenna and an integrated circuit as described above. The integrated circuit is electrically connected to the antenna and is used to transmit and receive electromagnetic wave signals. For example, as shown in FIG11, the electromagnetic wave sensor may include: a carrier, an integrated circuit as described in any of the above embodiments, and an antenna, etc. The integrated circuit may be disposed on the carrier; the antenna may be disposed on the carrier, or integrated with the integrated circuit as a single device disposed on the carrier (i.e., the antenna may be an antenna disposed in an AiP, AoP, or AoC structure); wherein the integrated circuit is connected to the antenna (i.e., the sensing chip or integrated circuit does not integrate an antenna, such as a conventional SoC), and is used to transmit and receive electromagnetic wave signals. The carrier may be a printed circuit board (PCB), and the corresponding transmission line may be a PCB trace.

[0107] This disclosure also provides a computer-readable storage medium including a computer program or instructions that, when executed, perform the methods described in any of the preceding embodiments.

[0108] This application also provides a terminal, which includes the radar, integrated circuit, or electromagnetic wave sensor described above. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, vehicles, drones, portable wearable devices, smart home devices, or intelligent robots, etc.

[0109] This disclosure also provides a terminal device, which can be manifested in the form of a general computing device. As shown in FIG12, the components of the terminal device may include, but are not limited to: at least one processing unit, at least one storage unit, a bus connecting different system components (including the storage unit and the processing unit), a display unit, etc. The storage unit stores program code, which can be executed by the processing unit to cause the processing unit to perform the methods described in this specification according to various exemplary embodiments of this disclosure. The storage unit may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) and / or a cache storage unit, and may further include a read-only memory unit (ROM).

[0110] The storage unit may also include a program / utility having a set (at least one) of program modules, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0111] A bus can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus that uses any of the various bus structures.

[0112] The terminal device can also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the terminal device can communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. The network adapter can communicate with other modules of the electronic device via a bus. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the terminal device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0113] For example, the terminal device in this embodiment may further include: a device body; and an electromagnetic wave sensor disposed on the device body as described in any of the above embodiments; wherein the electromagnetic wave sensor can be used to realize functions such as target detection and / or wireless communication.

[0114] Based on the above embodiments, in one optional embodiment of this disclosure, the electromagnetic wave sensor can be disposed outside the device body or inside the device body. In other optional embodiments of this disclosure, the electromagnetic wave sensor can be partially disposed inside the device body and partially disposed outside the device body. This disclosure does not limit the scope of the embodiments and may be determined as appropriate.

[0115] In an optional embodiment, the aforementioned device body can be a component or product applied in fields such as smart cities, smart homes, transportation, smart homes, consumer electronics, security monitoring, industrial automation, in-cabin detection (such as smart cockpits), medical devices, and healthcare. For example, the device body can be intelligent transportation equipment (such as automobiles, bicycles, motorcycles, ships, subways, trains, etc.), security equipment (such as cameras), liquid level / flow rate detection equipment, smart wearable devices (such as wristbands, glasses, etc.), smart home devices (such as robot vacuum cleaners, door locks, televisions, air conditioners, smart lights, etc.), various communication devices (such as mobile phones, tablets, etc.), as well as devices such as barriers, intelligent traffic lights, intelligent signs, traffic cameras, and various industrial robotic arms (or robots). It can also be various instruments for detecting vital signs parameters and various devices equipped with such instruments, such as in-cabin vital sign detection in automobiles, indoor personnel monitoring, smart medical devices, and consumer electronic devices.

[0116] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0117] Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include at least one of those features.

[0118] In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise expressly defined.

[0119] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0120] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A signal processing method, comprising: Based on the initial number of targets in the direction of arrival of the echo signal, the position information and amplitude of each target under the current number of targets are estimated. The current energy residual is calculated based on the position information and amplitude of the targets. If the energy residual is greater than a preset threshold, the current number of targets is increased, and the position information and amplitude of each target under the current number of targets are re-estimated until the current energy residual is less than the preset threshold. In estimating the position information and amplitude of the targets, the position information and amplitude of the targets are obtained by performing FFT processing and Chirp Z-transform processing on the target signals.

2. The method according to claim 1, wherein, The location information includes: angle or distance frequency or Doppler frequency.

3. The method according to claim 1, further comprising, before estimating the position information of each target given the current number of targets: The echo signal of a uniform linear array is obtained by padding the positions where there is no signal with zeros.

4. The method according to claim 1, wherein, The step of increasing the current number of targets and re-estimating the position information and magnitude of each target under the current number of targets includes: Increment the current number of targets by 1, use the position information and amplitude of each target obtained from the previous estimation to calculate the remaining signal in the echo signal as the signal of the new target, and obtain the position information and amplitude of the new target by performing FFT processing and Chirp Z-transform processing on the signal of the new target.

5. The method according to claim 4, after obtaining the position information and amplitude of the newly added target by performing FFT processing and Chirp Z-transform processing on the remaining signal, the method further includes: Repeat the following steps until the target's position information converges. For each target, with the position information and amplitude of other targets fixed, calculate the remaining signal in the echo signal based on the position information and amplitude of other targets as the signal of the current target. Perform FFT processing and Chirp Z-transform processing on the signal of the current target to obtain the new position information and amplitude of the current target.

6. The method according to claim 1, wherein, When the preset number of targets is 1, the step of obtaining the position information and amplitude of the target by performing FFT processing and Chirp Z-transform processing on the target signal includes: Perform FFT processing on the target signal to obtain the first frequency corresponding to the energy with the largest spectrum; A first frequency range is set according to the first frequency, and the target signal is subjected to Chirp Z-transform processing according to the first frequency range to obtain the second frequency and the corresponding amplitude corresponding to the energy with the largest spectrum. The amplitude is used as the amplitude of the current target. The position information of the target signal is obtained based on the second frequency and amplitude.

7. The method according to claim 6, wherein, The step of setting the first frequency range according to the first frequency includes: setting the first frequency range to the first frequency ± 1 / L, where L is the number of discrete data points processed by the FFT.

8. The method according to claim 1, wherein after increasing the current target number, the method further comprises: If the current number of targets reaches the preset maximum number of targets, the current signal processing flow will be terminated.

9. A signal processing apparatus, comprising a processor and a memory storing a computer program executable on the processor, wherein, When the processor executes the program, it implements the steps of the method as described in any one of claims 1-8.

10. A radar comprising a transceiver and a processor, the transceiver comprising: At least one antenna, wherein: the transceiver is used to transmit a detection signal and to receive an echo signal of the detection signal reflected by a target; the processor is used to perform the method as described in any one of claims 1-8.

11. An integrated circuit, comprising a signal transceiver and a processor, wherein: The transceiver is used to transmit a detection signal and to receive an echo signal reflected from the target; the processor is used to process the echo signal using the method described in any one of claims 1-8 to achieve target detection.

12. The integrated circuit according to claim 11, wherein, The integrated circuit is a millimeter-wave chip or a sensor chip.

13. An electromagnetic wave sensor, comprising: Carrier; The integrated circuit as described in any one of claims 11-12 is disposed on the carrier; as well as An antenna is disposed on the carrier, or the antenna and the integrated circuit are integrated into a single device and disposed on the carrier. The integrated circuit is connected to the antenna and is used to transmit electromagnetic wave signals and / or receive echo signals.

14. A terminal comprising the radar as claimed in claim 10, or the integrated circuit as claimed in any one of claims 11-12, or the electromagnetic wave sensor as claimed in claim 13.

15. A readable storage medium storing computer-executable instructions for performing the method of any one of claims 1-8.

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