Center frequency point acquisition and tracking method, integrated circuit, sensor and terminal device

Abstract

Embodiments of the present disclosure provide a signal center frequency point acquisition and tracking method, an integrated circuit, an electromagnetic wave sensor and a terminal device. The center frequency point tracking method of a to-be-tracked signal comprises: performing real-time conjugate multiplication on the to-be-tracked signal in the time domain by using a sweep signal, the sweep signal being a signal generated based on a lookup table; obtaining a frequency point with the maximum correlation value of the to-be-tracked signal and the sweep signal through correlation accumulation of a sliding window; and updating the frequency point with the maximum correlation value in real time as the center frequency point of the to-be-tracked signal at the current time.

Description

Technical Field

[0001] This disclosure relates to, but is not limited to, the field of signal processing technology, and particularly to a method for acquiring and tracking the center frequency of a signal, an integrated circuit, an electromagnetic wave sensor, and a terminal device. Background Technology

[0002] Currently, spectrum analysis is generally used to estimate the center frequency of a signal. In spectrum analysis, Fourier transform (FFT) is often used to find the center frequency of the signal by the peak value of the FFT spectrum. However, this method cannot guarantee both accuracy and real-time performance at the same time. Summary of the Invention

[0003] This disclosure provides a method for acquiring and tracking the center frequency of a signal, an integrated circuit, an electromagnetic wave sensor, and a terminal device, all with low complexity.

[0004] On one hand, this disclosure provides a method for tracking the center frequency of a signal to be tracked, including: performing real-time conjugate multiplication (or complex conjugate multiplication) of the signal to be tracked using a frequency sweep signal in the time domain, wherein the frequency sweep signal is a signal generated based on a lookup table; obtaining the frequency point with the largest correlation value between the signal to be tracked and the frequency sweep signal through correlation accumulation using a sliding window; and updating the frequency point with the largest correlation value as the center frequency of the signal to be tracked at the current moment in real time.

[0005] In an exemplary embodiment, the frequency point with the largest correlation value may be the frequency point corresponding to the global maximum value of the correlation accumulation result, or the frequency point corresponding to the middle data in the window corresponding to the maximum value of the correlation accumulation result.

[0006] In an exemplary embodiment, the frequency sweep signal is a periodic signal, and the frequency sweep signal is pre-generated in the following manner: a portion of the data within one period of the frequency sweep signal is pre-saved, and other data within one period of the frequency sweep signal is calculated and generated based on the saved portion of the data.

[0007] In an exemplary embodiment, the step of pre-saving a portion of the data within one cycle of a frequency sweep signal includes: pre-saving data for 1 / 4 cycle or 1 / 2 cycle of a frequency sweep signal.

[0008] In an exemplary embodiment, the step of calculating and generating other data within one cycle of the frequency sweep signal based on the saved partial data includes: calculating and generating other data within one cycle of the frequency sweep signal according to one or more of the following calculation methods: reverse order, conjugate, and reverse conjugate.

[0009] In an exemplary embodiment, a full-cycle sweep signal can be constructed during tracking by pre-saving data for 1 / 4 cycle of a sweep signal, based on table lookup, reversal, conjugate, and reversed conjugate.

[0010] In an exemplary embodiment, the swept frequency signal is a frequency-modulated continuous wave signal.

[0011] In an exemplary embodiment, obtaining the frequency point with the largest correlation value between the signal to be tracked and the frequency sweep signal through correlation accumulation via a sliding window includes: obtaining the frequency point with the largest correlation value between the signal to be tracked and the frequency sweep signal through correlation accumulation via a sliding window within half a frequency sweep period of the frequency sweep signal.

[0012] In an exemplary embodiment, the window length of the sliding window is an odd number.

[0013] In an exemplary embodiment, the frequency point with the largest correlation value is the frequency point corresponding to the maximum value of the correlation accumulation result; or, the frequency point with the largest correlation value is the frequency point of the signal to be tracked corresponding to the middle data of the window corresponding to the maximum value of the correlation accumulation result.

[0014] In an exemplary embodiment, the signal to be tracked is the received intermediate frequency signal or baseband signal of the UWB device.

[0015] In an exemplary embodiment, updating the frequency point with the largest correlation value to the center frequency point of the signal to be tracked at the current moment in real time includes: using a filter to update the frequency point with the largest correlation value to the center frequency point of the signal to be tracked at the current moment in real time.

[0016] In an exemplary embodiment, the bandwidth of the sweep signal may include the frequency range of the center frequency drift of the signal to be tracked; for example, the bandwidth of the sweep signal may be slightly greater than or equal to the frequency range of the center frequency drift of the signal to be tracked.

[0017] On the other hand, this disclosure also provides a method for obtaining the center frequency of a signal, comprising: performing time-domain correlation operations, such as inner product calculation (e.g., conjugate multiplication), on the signal to be processed using a frequency sweep signal in the time domain to obtain a signal correlation value; and taking the frequency point with the largest signal correlation value as the center frequency of the signal to be processed. The signal to be processed may be a communication or radar received signal.

[0018] On the other hand, embodiments of this disclosure also provide an integrated circuit, including: The signal transmitting module is configured to transmit electromagnetic wave signals; A signal receiving module is configured to receive the electromagnetic wave signal, or the echo signal formed by reflection and / or scattering; and The processing module is configured to track the center frequency of the electromagnetic wave signal or the echo signal according to the method described above.

[0019] In an exemplary embodiment, the integrated circuit is a UWB chip or a sensor chip.

[0020] On the other hand, this disclosure also provides an electromagnetic wave sensor, including: a carrier; an integrated circuit as described above disposed on the carrier; an antenna 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 the electromagnetic wave signal and / or receive the electromagnetic wave signal or echo signal.

[0021] In another aspect, embodiments of this disclosure also provide a terminal device, including: a device body; and an integrated circuit as described above, or an electromagnetic wave sensor as described above, disposed on the device body.

[0022] It should be noted that the signal to be tracked or the signal to be processed in the embodiments of this application can be a useful signal or an interference signal, etc.; for example, the signal to be tracked or the signal to be processed can be a useful signal such as a communication and / or radar signal received by a superheterodyne receiver. The method provided in this embodiment can track the center frequency of the signal in real time so as to complete demodulation at the receiving end; the signal to be tracked or the signal to be processed can also be an interference signal, that is, the solution provided in this embodiment can track the center frequency of the interference signal in real time, thereby realizing interference cancellation and other operations at the receiving end.

[0023] Optionally, the technical solutions in this application embodiment can be used for tracking time-varying intermediate frequency signals or tracking signals with a fixed center frequency. For example, the signal to be tracked or processed in this application embodiment can be a signal whose center frequency changes within a certain range due to factors such as frequency errors in the transceiver crystal, signal transmission path, or environmental changes; it can also be a scenario where the intermediate frequency of a signal with a fixed center frequency changes due to factors such as frequency errors or interference in the transceiver crystal, such as a zero-IF transmitted signal, or a received signal that is a non-zero intermediate frequency signal (such as a low-IF signal or a high-IF signal) due to frequency errors in the transceiver crystal.

[0024] It should be noted that the signal to be tracked and the frequency sweep signal in the embodiments of this application can be complex signals (such as IQ signals, such as the baseband signal after IQ demodulation of a UWB receiver, etc.), while if the signal to be tracked and the frequency sweep signal are real signals, the corresponding conjugate multiplication operation can be adjusted to multiplication or mixing processing.

[0025] The method in this embodiment is simple to implement and can achieve high-precision signal center frequency tracking with low complexity. Since it uses time-domain correlation to track the intermediate frequency of the signal, it can improve the real-time performance of tracking at the same accuracy.

[0026] Other features and advantages of this disclosure will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the disclosure. Other advantages of this disclosure may be realized and obtained by means of the embodiments described in the description, claims, and drawings. Attached Figure Description

[0027] The accompanying drawings are provided to illustrate the technical solutions of this disclosure and form part of the specification. They are used together with the embodiments of this disclosure to explain the technical solutions of this disclosure and do not constitute a limitation on the technical solutions of this disclosure. The shapes and sizes of the components in the drawings do not reflect actual proportions and are only intended to illustrate the content of this disclosure.

[0028] Figure 1 This is a flowchart of a method for determining the center frequency point according to an embodiment of the present invention; Figure 2 A flowchart of a method for tracking the center frequency of a signal to be tracked, provided in an embodiment of this disclosure; Figure 3 A flowchart of another signal center frequency tracking method provided in this disclosure embodiment; Figure 4 This is a schematic diagram of periodic storage of a frequency sweep signal according to an embodiment of the present disclosure; Figure 5A This is an embodiment of the present disclosure. Figure 4 The diagram shows the frequency of the sweep signal. Figure 5B This is an embodiment of the present disclosure. Figure 4 The diagram shows the angle of the sweep frequency signal. Figure 6 This is a tracking effect diagram of an embodiment of the present disclosure; Figure 7 A flowchart illustrating a method for obtaining the center frequency of a signal, provided in an embodiment of this disclosure; Figure 8 This is a schematic diagram of an application device according to an embodiment of the present disclosure. Detailed Implementation

[0029] This disclosure 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 the detailed description, 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.

[0030] 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 the method or process does not depend on the specific order of steps described herein. 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 relating to the method and / or process should not be limited to the steps performed in the order written, 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 disclosed herein.

[0031] Related techniques generally employ frequency domain analysis to estimate the center frequency of a signal. In spectral analysis, the FFT method is frequently used to find the signal's center frequency by analyzing the peak values ​​of the FFT. However, improving the accuracy of this method requires a sufficiently large FFT window length, thus making it impossible to simultaneously guarantee accuracy and real-time performance.

[0032] Specifically, embodiments of this disclosure provide a method for determining the center frequency point, such as... Figure 1 As shown, the following steps may be included: Step 11: Use a pre-generated sweep signal to perform real-time sweep of the received signal. At each moment of sweeping, calculate the correlation value between the received signal and the sweep signal, and accumulate the correlation value to obtain the correlation accumulation result at the current moment. Step 12: Determine the center frequency of the received signal at the current moment based on the relevant accumulation results.

[0033] The method in this embodiment is simple to implement and can achieve high-precision signal center frequency tracking with low complexity. Since it uses time-domain correlation to track the intermediate frequency of the signal, it can significantly improve the real-time performance of tracking at the same level of accuracy.

[0034] In an exemplary embodiment, when the sweep signal is a periodic signal, the sweep signal can be pre-generated in the following manner: a portion of the data within one period of the sweep signal is pre-saved, and other data within one period of the sweep signal is calculated based on the saved portion of the data. For example, data for 1 / 4 period of the sweep signal can be pre-saved in a list. During tracking, this 1 / 4 period of data is obtained based on a table lookup, and then a complete period of the sweep signal is constructed through calculations such as reversal, conjugate, and reverse conjugate.

[0035] In an exemplary embodiment, the calculation of the correlation value between the received signal and the swept frequency signal in step 11 above can be performed as follows: The correlation value between the received signal and the swept frequency signal is obtained by performing a conjugate multiplication. Conjugate multiplication can identify the frequency point of the received signal that has a higher correlation with the frequency point of the swept frequency signal. For example, the frequency difference between the received signal and the swept frequency signal can be converted into phase information through conjugate multiplication, and phase coherence can be detected by sliding window accumulation, thereby identifying the frequency point with the highest correlation.

[0036] In an exemplary embodiment, the accumulation of the relevant values ​​in step 11 above can be performed in the following way: the relevant values ​​are accumulated by sliding window, so as to find the window with the largest accumulated relevant value.

[0037] In an exemplary embodiment, step 12 above, determining the center frequency of the received signal at the current moment based on the correlation accumulation result, specifically includes: selecting the frequency point corresponding to the maximum value of the correlation accumulation result as the frequency point most correlated with the swept frequency signal, which is the center frequency of the received signal. When a sliding window accumulation method is used, the window corresponding to the maximum value of the correlation accumulation result can be selected, and the received signal frequency point corresponding to the middle data in the window is the center frequency of the received signal.

[0038] In an exemplary embodiment, after determining the center frequency of the received signal at the current moment based on the correlation accumulation result, the method further includes: updating the center frequency using an alpha filter to improve the robustness of the signal receiving system.

[0039] Specifically, this disclosure also provides a method for tracking the center frequency of a signal to be tracked, such as... Figure 2 As shown, it includes the following steps: Step 21: In the time domain, a frequency sweep signal is used to perform real-time conjugate multiplication on the signal to be tracked. The frequency sweep signal is a signal generated based on a lookup table. Multiplying the signal to be tracked by its conjugate with the swept frequency signal yields the correlation value between the two signals. This conjugate multiplication identifies the frequency point of the signal to be tracked that has a higher correlation with the swept frequency signal, thus facilitating frequency tracking.

[0040] Step 22: Obtain the frequency point with the largest correlation value between the signal to be tracked and the swept frequency signal by performing correlation accumulation through a sliding window; The sliding window correlation accumulation refers to the sliding window accumulation of the correlation values ​​(i.e., the conjugate multiplication results) obtained in step 21. By accumulating the correlation values ​​using a sliding window method, it is possible to find the window with the largest correlation accumulation value.

[0041] Step 23: Update the frequency point with the largest correlation value to the center frequency point of the signal to be tracked at the current moment in real time.

[0042] The method in this embodiment is simple to implement and has low complexity. It obtains the sweep frequency signal through a simple table lookup operation, and tracks the frequency point by correlating the sweep frequency signal with the signal to be tracked in the time domain. This method can achieve high accuracy with less register overhead.

[0043] In an exemplary embodiment, the sweep signal is a periodic signal, which can be pre-generated by pre-saving a portion of the data within one period of the sweep signal, and calculating the remaining data within one period of the sweep signal based on the saved portion of the data. For example, the portion of the data may be: pre-saving data for 1 / 4 or 1 / 2 period of the sweep signal. The data for the complete period is calculated using the pre-saved 1 / 4 period, or the data for the complete period is calculated based on the pre-saved 1 / 2 period. To obtain the sweep signal used in time-domain correlation, this embodiment uses a periodic sweep signal; therefore, only a portion of the periodic signal needs to be saved. For example, a portion of the periodic signal can be saved in a list, and the remaining portion can be obtained by looking up known data in the table and then by simple calculation. This allows for achieving the required accuracy with less register overhead; that is, under the same accuracy conditions, this embodiment has lower hardware overhead. The simple calculation may include one or more of the following: reverse order, conjugate, and reverse conjugate.

[0044] In order to achieve tracking, the frequency range of the sweep signal used in this embodiment covers the frequency range of the signal to be tracked.

[0045] Optionally, the periodic sweep signal used is a frequency-modulated continuous wave signal. In other embodiments, other signals whose frequencies vary over time can be selected as the sweep signal to achieve frequency tracking.

[0046] In an exemplary embodiment, the frequency point with the largest correlation value in step 23 above can be, for example, the frequency point corresponding to the maximum value of the correlation accumulation result, that is, the frequency point where the signal to be tracked is most correlated with the swept frequency signal, and this frequency point is the center frequency point of the signal to be tracked. Alternatively, when using a sliding window accumulation method, the frequency point with the largest correlation value in step 23 above can also be the frequency point of the signal to be tracked corresponding to the middle data in the window corresponding to the maximum value of the correlation accumulation result, and this frequency point is the center frequency point of the signal to be tracked. Simulation can be used to determine which of the above methods can more accurately track the center frequency point of the signal.

[0047] In an exemplary embodiment, within half a sweep cycle of the sweep signal, the frequency point with the highest correlation value between the signal to be tracked and the sweep signal can be obtained by correlation accumulation through a sliding window. This allows for rapid tracking of the signal's center frequency, resulting in good real-time performance.

[0048] For example, the window length of a sliding window can be set to an odd number. By setting the window length to an odd number, it is guaranteed that a center point can always be found in the window.

[0049] In an exemplary embodiment, in step 23 above, a filter can be used to update the frequency point with the largest correlation value to the center frequency point of the signal to be tracked at the current moment, which can further improve the robustness of the signal receiving system.

[0050] The following application example provides a detailed explanation of the signal center frequency tracking method disclosed herein. The processing procedure is as follows: Figure 3 As shown.

[0051] Taking a time-varying baseband signal with a center frequency as an example, this baseband signal undergoes up-conversion at the transmitter (TX) and then over-the-air transmission. After down-conversion at the receiver (RX), a zero intermediate frequency (ZIF) received signal is obtained. However, the ZIF frequency will drift between -f0 and +f0 within a frame. A zero-IF signal refers to a signal that has been converted to a fixed intermediate frequency after processing by the radio frequency front-end in a wireless communication receiver. Converting the received signal to an intermediate frequency is for ease of subsequent tracking. In this case, the received signal serves as the signal to be tracked, and the intermediate frequency of the received signal can be dynamically tracked using the method described in the aforementioned embodiment, enabling the subsequent receiver baseband module to correctly process the signal. Specifically, this includes steps 31-34.

[0052] Step 31: Generate a frequency sweep signal; In this embodiment, to reduce complexity, a lookup table method is used to generate the frequency sweep signal. Specifically, only complex data of 1 / 4 period + 1 ns needs to be stored. This can generate a frequency sweep signal, such as Figure 4 As shown, during generation: For the first 1 / 4 period 0 to 128, the data stored in the table can be used: [0:128], totaling 129 ns of complex data; For the second 1 / 4 cycle 128–256, use the reverse order of the data in the table: [128:0]; For the third 1 / 4 cycle 256–384, use the conjugate of the data in the table: conj([0:128]); For the fourth 1 / 4 cycle 384~512, use the reverse conjugate of the data in the table: conj([128:0]).

[0053] Optional, based on Figure 4 As shown, this embodiment may also include a phase smoothing mechanism, such as using phase interpolation or Overlap-Add at the data splicing point to ensure the phase continuity of the sweep frequency signal.

[0054] The swept frequency waveform can be obtained directly through a simple table lookup operation, reducing complexity while maintaining the same level of accuracy. The same accuracy can be achieved with less register overhead. For example, compared to digital frequency conversion methods such as digital mixers or coordinate rotation digital computers, the table lookup method reduces one processing module and lowers hardware costs.

[0055] The frequency range of the generated sweep signal covers the frequency range of the received signal to ensure that the received signal can be swept. In this embodiment, the center frequency of the received signal is 0, but it has a deviation of ±10MHz, thus it can generate a frequency range such as... Figure 5A , Figure 5B The frequency modulated continuous wave (FMCW) signal shown is... Figure 5A This is a frequency diagram of the sweep signal. Figure 5B This is a schematic diagram of the sweep signal angle. In this example, the maximum frequency of the sweep signal is f0 = 10MHz, the sweep range is -10MHz to 10MHz, the sweep period is 512ns, and the sampling rate is 1GHz. The sweep period and sampling rate described here are merely examples; those skilled in the art can set them as needed, such as increasing or decreasing the sweep period and the sampling rate. In other embodiments, if the received signal is not a zero-IF signal, the sweep range of the generated sweep signal can be adjusted according to the frequency drift range of the received signal.

[0056] Step 32: Use the generated sweep signal to sweep the received signal. For example, the sweep process includes: multiplying the received signal and the sweep signal by their conjugates to obtain the correlation value y(t) between the received signal and the sweep signal. y(t) = x(t) * conj(m(t)) Where x(t) is the received signal, m(t) is the sweep frequency signal, and conj() represents finding the conjugate of the sweep frequency signal.

[0057] When performing conjugate multiplication, the result is larger when the frequency of the received signal matches the frequency of the swept signal, indicating a stronger correlation between the two signals. Therefore, conjugate multiplication can be used to find the frequency of the received signal that has a higher correlation with the swept signal.

[0058] In this example, the period of one frequency sweep is 512ns, and the frequency accuracy is 10M / 128 = 78.125KHz.

[0059] Step 33: Perform a sliding window correlation accumulation on the above correlation values ​​to obtain the frequency point closest to the intermediate frequency of the received signal; The window length is set to 2w+1, where w is a positive integer greater than or equal to 1 (the specific value can be set based on the actual application scenario). The sliding window step size is preferably 1. This is the cumulative value related to frequency point m(f). for: By setting the window length to an odd number, a center point can always be found within the window. Accumulating the correlation values ​​using a sliding window method yields a peak window of accumulated values, where the accumulated correlation value is at its maximum. In this example, the frequency of the swept signal corresponding to the center point of this window with the maximum accumulated correlation value is used as the intermediate frequency (IF) of the tracked received signal. The largest point The center frequency of the signal is updated to the frequency point with the largest correlation value. .

[0060] A shorter window length results in better real-time performance, while a longer window length results in higher accuracy. The window length can be set as needed to balance real-time performance and accuracy.

[0061] Since a single frequency sweep cycle completes the process from +10MHz to -10MHz and then from -10MHz to +10MHz, a single frequency sweep and peak finding operation can be completed in half a cycle. That is, within half a sweep cycle, the frequency point with the highest signal correlation value, i.e., the center frequency point of the signal, can be found.

[0062] Step 34: Update the obtained center frequency.

[0063] This step is optional. A filter (e.g., an alpha filter) can be used to update the center frequency f(t) to further improve the robustness of the system. One update method is as follows: in, This is the center frequency point obtained in this calculation. The center frequency point obtained in the previous calculation. For weights, 0 < <1.

[0064] The alpha filter is an exponentially weighted moving average filter, used in this example to smooth frequency sequence data. In the alpha filter, different weights are assigned to the center frequency point calculated in the current iteration and the center frequency point calculated in the previous iteration. The weight of the center frequency point calculated in the current iteration can be higher than the weight of the center frequency point calculated in the previous iteration, by adjusting... The value can adjust the degree to which the filter depends on historical values, thereby affecting the smoothing effect and the response speed to rapid changes.

[0065] use Figure 5A and Figure 5B The frequency sweep signal shown can complete the process from +10MHz to -10MHz and then from -10MHz to +10MHz in one cycle. A single sweep cycle of 512ns yields a frequency accuracy of 10MHz / 128 = 78.125kHz. Using the generated frequency sweep signal to track the received signal in this embodiment, a single frequency sweep and peak finding operation can be completed in half a cycle.

[0066] In an exemplary embodiment, the intermediate frequency of the signal varies sinusoidally within the range of -10MHz to 10MHz, and w = 5. For example, the simulation results of intermediate frequency tracking are as follows: Figure 6 As shown, with an initial intermediate frequency difference of 10MHz, the scheme of this embodiment can be quickly adjusted to the vicinity of the intermediate frequency point, and accurately track the center frequency point of the signal in real time in subsequent signals.

[0067] The frequency tracking method in this embodiment has no requirements on the waveform of the transmitted signal.

[0068] This embodiment's method can track signals with a fixed center frequency (which can be 0 or non-zero), as well as signals whose center frequency shifts over time. For example, due to frequency errors between the crystal oscillators at the transmitting and receiving ends, the intermediate frequency (IF) may be fixed at a non-zero position, such as in analog-to-digital converter (ADC) signals where the IF is fixed at a non-zero position. In this case, the method of this embodiment can converge to the signal's center frequency with relatively high accuracy. As another example, due to frequency errors between the crystal oscillators at the transmitting and receiving ends, the IF may experience time-varying frequency drift, meaning the center frequency of the received signal (Rx) will change within a certain range, such as in ADC signals where the IF changes over time. In this case, the method of this embodiment can track the signal's center frequency with relatively high accuracy in real time. For instance, when the transmitted signal is known and there is a fixed frequency difference between the received and transmitted signals, this embodiment's method can track and obtain the center frequency of the received signal, thereby obtaining the frequency difference between the received and transmitted signals, facilitating subsequent signal processing, such as compensation. For example, if the transmitted signal is known, but the received signal is jittery due to interference or other reasons, the method in this embodiment can track and obtain the center frequency of the received signal, thereby removing the interference during subsequent signal processing.

[0069] The method disclosed herein, by tracking the intermediate frequency of the signal in the time domain, significantly improves the real-time performance of tracking compared to spectrum analysis methods using the FFT method, while maintaining the same accuracy; that is, it can quickly track changes in the center frequency. Furthermore, during center frequency tracking, a lookup table method is used to generate a frequency sweep wave for frequency sweeping operations, achieving high accuracy with relatively low register overhead.

[0070] The method disclosed herein can be applied, for example, to a receiving device employing Ultra Wide Band (UWB) technology, or to a radar device that transmits electromagnetic wave signals. The signal to be tracked can be a received intermediate frequency signal or a baseband signal, or other signals that need to be tracked.

[0071] This example presents a low-complexity method for tracking the center frequency of a signal in the time domain. This method can be applied to address technical challenges in superheterodyne receivers, such as the need for real-time tracking of the signal's center frequency for demodulation at the receiver, or real-time tracking of the center frequency of interference for interference cancellation. This example method significantly improves the real-time performance of tracking while maintaining the same accuracy by using time-domain correlation to track the intermediate frequency (IF), rather than spectral analysis. Furthermore, to address the issue of generating a frequency sweep waveform for time-domain correlation, this example proposes a low-complexity scheme that directly obtains the sweep waveform through a simple table lookup operation, and then correlates it with the signal to track the frequency. This method achieves high accuracy with minimal storage overhead.

[0072] This disclosure also provides a method for obtaining the center frequency of a signal, such as... Figure 7 As shown, it includes the following steps: Step 41: In the time domain, a frequency sweep signal is used to perform time-domain correlation on the signal to be processed to obtain the signal correlation value; Step 42: Take the frequency point with the largest correlation value of the signal as the center frequency point of the signal to be processed.

[0073] In this example method, the signal to be processed is... Figure 1 The received signal in the process shown is, i.e. Figure 2 The signal to be tracked in the process shown.

[0074] Using the method in this embodiment, the center frequency of a signal can be obtained with low complexity and high accuracy. This example method is similar to... Figure 1 or Figure 2 or Figure 3 The example method shown is similar, the difference being that this embodiment does not require real-time tracking of the center frequency, making it suitable for scenarios where the center frequency needs to be determined. Specific details can be found in the descriptions of the preceding embodiments, and will not be repeated here.

[0075] Figure 8 A schematic diagram of a digital receiver is provided. The signal received by the antenna is sampled by an ADC to obtain a digital signal, which is then filtered and input to an interference detection module. The interference detection module can obtain the intermediate frequency (IF) point of the received signal using the IF tracking method provided in this embodiment. Based on the IF point of the received signal and the known frequency point of the transmitted signal, the interference signal can be calculated. Interference cancellation is performed based on the calculated interference signal, and the interference-free received signal is sent to the baseband processing module for further processing. The baseband processing module can be used to perform sampling, Fast Fourier Transform (FFT), Constant False Alarm Rate (CFAR), and Direction of Arrival (DoA) estimation on the received signal.

[0076] This disclosure also provides an integrated circuit, which may include: a signal transmitting module configured to transmit electromagnetic wave signals; a signal receiving module configured to receive the electromagnetic wave signals (e.g., ranging mode of a UWB device), or echo signals formed by reflection and / or scattering (e.g., radar mode of a radar device or a UWB device); and a processing module configured to perform signal tracking processing on the electromagnetic wave signals or the echo signals according to this embodiment to obtain the intermediate frequency point of the received signal.

[0077] Alternatively, in an exemplary embodiment, the integrated circuit may be a UWB chip or die or a sensor chip.

[0078] This disclosure also provides an integrated circuit, which 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 RF transmission signals and receive electromagnetic wave signals or echo signals. The analog signal processing module is used to down-convert the electromagnetic wave signals or echo signals to obtain intermediate frequency (IF) signals. The digital processing module is used to perform analog-to-digital conversion on the IF signals to obtain digital signals. The digital signals are then processed based on the signal tracking method described in this disclosure to obtain the IF frequency point of the received signal. For example, this integrated circuit may be a UWB chip (chip or die).

[0079] In some optional embodiments, the integrated circuit may be an AiP (Antenna-In-Package) chip structure, an AoP (Antenna-On-Package) chip structure, an AoC (Antenna-On-Chip) chip structure, or a RoP (Radiator on Package) structure.

[0080] 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, 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, AoC, or RoP 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, via, or waveguide, etc.

[0081] This disclosure provides a terminal device that may include: a device body; and an electromagnetic wave sensor, as described above, disposed on the device body; wherein the electromagnetic wave sensor is used for target detection and / or communication to provide reference information for the operation of the device body. Alternatively, the terminal device may include a device body and an integrated circuit, as described in any of the above embodiments, disposed on the device body.

[0082] 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.

[0083] 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, digital keys, indoor positioning, in-cabin detection (such as smart cockpits), medical devices, and healthcare. For example, the device body can be intelligent transportation equipment (such as cars, 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-car vital sign detection, indoor personnel monitoring, smart medical devices, and consumer electronic devices.

[0084] It should be noted that when the center frequency of the transmitted signal changes at a certain moment, the solution provided in this application can promptly obtain the center frequency of the change, and processing can be performed based on the obtained center frequency to suppress or eliminate the influence of the center frequency change on the output intermediate frequency signal or the input of signal processing (such as FFT) during subsequent Rx processing. This represents a significant improvement compared to not using the solution in this application. Furthermore, in engineering implementation, the time-domain frequency tracking solution based on this application can be applied to the multiplication coefficients used for tracking the signal center frequency.

[0085] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] The above-described embodiments merely illustrate preferred embodiments of the present invention and the technical principles employed. While the descriptions are detailed, they should not be construed as limiting the scope of the invention. Various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments. Many other equivalent embodiments may be included without departing from the inventive concept, and the scope of protection of this patent is determined by the appended claims.

[0087] 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 media 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.

Claims

1. A method for tracking the center frequency of a signal to be tracked, characterized in that, include: In the time domain, a frequency sweep signal is used to perform real-time conjugate multiplication of the signal to be tracked. The frequency sweep signal is generated based on a lookup table. By using correlation accumulation through a sliding window, the frequency point with the largest correlation value between the signal to be tracked and the frequency sweep signal is obtained; as well as The frequency point with the largest correlation value is updated in real time to the center frequency point of the signal to be tracked at the current moment.

2. The method according to claim 1, characterized in that, The frequency sweep signal is a periodic signal, and the frequency sweep signal is pre-generated using the following method: A portion of the data within one cycle of a frequency sweep signal is pre-saved, and other data within one cycle of the frequency sweep signal is calculated and generated based on the saved portion of the data.

3. The method according to claim 2, characterized in that, The pre-saved portion of data within one cycle of a frequency sweep signal includes: Save data for 1 / 4 or 1 / 2 cycle of a sweep frequency signal in advance.

4. The method according to claim 2, characterized in that, The step of calculating and generating other data within one cycle of the frequency sweep signal based on the saved partial data includes: Other data within one cycle of the swept frequency signal are generated according to one or more of the following calculation methods: reverse order, conjugate, and reverse conjugate.

5. The method according to claim 1, characterized in that, The frequency sweep signal is a frequency-modulated continuous wave signal.

6. The method according to claim 1, characterized in that, The step of obtaining the frequency point with the largest correlation value between the signal to be tracked and the frequency sweep signal by correlation accumulation through a sliding window includes: obtaining the frequency point with the largest correlation value between the signal to be tracked and the frequency sweep signal by correlation accumulation through a sliding window within half a frequency sweep period of the frequency sweep signal.

7. The method according to claim 1 or 6, characterized in that, The length of the sliding window is an odd number.

8. The method according to claim 1 or 6, characterized in that, The frequency point with the largest correlation value is: the frequency point corresponding to the maximum value of the correlation accumulation result; or The frequency point with the largest correlation value is the frequency point of the signal to be tracked corresponding to the middle data in the window corresponding to the maximum value of the correlation accumulation result.

9. The method according to claim 1, characterized in that, The signal to be tracked is the intermediate frequency signal or baseband signal received by the UWB device.

10. The method according to claim 1, characterized in that, The step of updating the frequency point with the largest correlation value to the center frequency point of the signal to be tracked at the current moment in real time includes: using a filter to update the frequency point with the largest correlation value to the center frequency point of the signal to be tracked at the current moment in real time.

11. A method for obtaining the center frequency of a signal, characterized in that, include: In the time domain, a frequency sweep signal is used to perform time-domain correlation on the signal to be processed to obtain the signal correlation value; The frequency point with the largest correlation value of the signal is taken as the center frequency point of the signal to be processed.

12. An integrated circuit, characterized in that, include: The signal transmitting module is configured to transmit electromagnetic wave signals; The signal receiving module is configured to receive the electromagnetic wave signal, or the echo signal formed by reflection and / or scattering; as well as The processing module is configured to track the center frequency of the electromagnetic wave signal or the echo signal according to the method described in any one of claims 1-10.

13. The integrated circuit according to claim 12, characterized in that, The integrated circuit is a UWB chip or a sensor chip.

14. An electromagnetic wave sensor, characterized in that, include: Carrier; The integrated circuit as described in claim 12 or 13 is disposed on the carrier; 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 the electromagnetic wave signal and / or receive the electromagnetic wave signal or echo signal.

15. A terminal device, characterized in that, include: Equipment body; as well as The integrated circuit as described in claim 12 or 13, or the electromagnetic wave sensor as described in claim 14, is disposed on the device body.

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