Methods, apparatuses, electronic devices, storage media and products for generating digital signals

Abstract

This application provides a method, apparatus, electronic device, storage medium, and product for generating digital signals. The method includes: acquiring sampling information; determining the phase increment of each sampling point of the digital signal based on the acquired sampling information; determining the target phase of each sampling point sequentially using the phase increment corresponding to each sampling point; mapping the target phase of each sampling point in a first interval to a second interval with a smaller value range according to a pre-configured phase conversion relationship to obtain the corresponding converted phase; and determining the amplitude value of the digital signal corresponding to each sampling point based on the converted phase of each sampling point, thus completing the generation of the digital signal. This application does not rely on dedicated hardware devices for signal generation; it can achieve digital signal generation through streamlined calculations, thereby reducing hardware dependence and making it more suitable for miniaturized application scenarios.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus, electronic device, storage medium and product for generating digital signals. Background Technology

[0002] In digital communication, the generation of digital signals is a crucial technical step. Taking linear frequency modulation (Chirp) signals as an example, the accurate generation of Chirp signals is a key foundation for achieving stable signal applications and ensuring communication transmission quality and operational reliability.

[0003] In related technologies, the receiver of the terminal typically generates the chirp signal by deploying an external Direct Digital Frequency Synthesis (DDFS) or a Phase-Locked Loop (PLL).

[0004] However, the above methods are limited in their applicability and are not suitable for miniaturized terminals. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, storage medium, and product for generating digital signals, aiming to improve the applicability of various scenarios and enhance the technical effect of miniaturized terminals.

[0006] In a first aspect, embodiments of this application provide a method for generating a digital signal, comprising:

[0007] Obtain sampling information;

[0008] The phase increment of each sampling point of the digital signal is determined based on the sampling information.

[0009] The target phase of each sampling point is determined based on the phase increment of each sampling point, and the range of the target phase is in the first interval;

[0010] Based on the pre-configured phase conversion relationship, the conversion phase corresponding to the target phase of each sampling point mapped to the second interval is determined, and the value range of the second interval is smaller than that of the first interval;

[0011] The amplitude value of each sampling point of the digital signal is determined based on the conversion phase of each sampling point in order to generate the digital signal.

[0012] In one possible implementation, the sampling information includes: waveform parameters, sweep period, sampling parameters, and number of sampling points. Determining the phase increment of each sampling point of the digital signal based on the sampling information includes:

[0013] For the nth sampling point, the first parameter of the nth sampling point is determined based on the waveform parameters and the sampling parameters. , The number of sampling points;

[0014] The second parameter of the nth sampling point is determined based on the sampling parameters, the frequency sweep period, and the nth sampling point.

[0015] The first parameter is multiplied by the second parameter, and the result of the multiplication is determined as the phase increment of the nth sampling point.

[0016] In one possible implementation, determining the target phase of each sampling point based on the phase increment of each sampling point includes:

[0017] The initial phase of the first sampling point is determined based on the waveform parameters, the frequency sweep period, and the sampling parameters.

[0018] Perform a modulo operation on the initial phase of the first sampling point to obtain the target phase of the first sampling point;

[0019] The target phase of each sampling point is determined by iterative calculation based on the target phase of the first sampling point and the phase increment of each sampling point.

[0020] In one possible implementation, the interval range corresponding to the phase conversion relationship is the value range of the first interval, and the first interval is divided into multiple sub-intervals, each sub-interval corresponding to a mapping relationship between the target phase and the converted phase;

[0021] The step of determining the target phase mapping of each sampling point to the corresponding transformed phase of the second interval according to the pre-configured phase transformation relationship includes:

[0022] Based on the target phase of each sampling point, matching is performed in the multiple sub-intervals to determine the target sub-interval where each sampling point is located.

[0023] Based on the mapping relationship between the target phase and the transformed phase in the target sub-interval where each sampling point is located, the transformed phase corresponding to the target phase of each sampling point is determined, and the transformed phase corresponds to the value range of the second interval.

[0024] In one possible implementation, determining the amplitude value of each sampling point of the digital signal based on the transition phase of each sampling point includes:

[0025] The trigonometric function of each sampling point is determined based on the transformation phase of each sampling point.

[0026] The trigonometric functions of each sampling point are solved based on a preset approximation algorithm to determine the approximate values ​​of the trigonometric functions of each sampling point.

[0027] The amplitude value of each sampling point of the digital signal is determined based on the approximate trigonometric function values ​​of each sampling point.

[0028] In one possible implementation, determining the amplitude value of each sampling point of the digital signal based on the trigonometric function approximation values ​​of each sampling point includes:

[0029] The approximate trigonometric function values ​​of each sampling point are input into the preset waveform generation algorithm of the digital signal to obtain the output results of each sampling point;

[0030] The output results of each sampling point are determined as the amplitude value of each sampling point of the digital signal.

[0031] Secondly, embodiments of this application provide a digital signal generation apparatus, comprising:

[0032] The acquisition module is used to acquire sampling information;

[0033] The determination module is used to determine the phase increment of each sampling point of the digital signal based on the sampling information;

[0034] The determining module is further configured to determine the target phase of each sampling point based on the phase increment of each sampling point, wherein the range of the target phase is in the first interval;

[0035] The determining module is further configured to determine the transformation phase corresponding to the target phase of each sampling point mapped to the second interval according to the pre-configured phase transformation relationship, wherein the value range of the second interval is smaller than that of the first interval;

[0036] The determining module is further configured to determine the amplitude value of each sampling point of the digital signal based on the conversion phase of each sampling point, so as to generate the digital signal.

[0037] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0038] The memory stores computer-executed instructions;

[0039] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0040] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0041] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0042] The digital signal generation method, apparatus, electronic device, storage medium, and product provided in this application acquire sampling information, determine the phase increment of each sampling point of the digital signal based on the acquired sampling information, and determine the target phase of each sampling point sequentially using the phase increment corresponding to each sampling point. Then, according to a pre-configured phase conversion relationship, the target phase of each sampling point in the first interval is mapped to a second interval with a smaller value range to obtain the corresponding converted phase. Based on the converted phase of each sampling point, the amplitude value of the digital signal corresponding to each sampling point is determined, thus completing the generation of the digital signal. This application relies on sampling information to complete the phase increment calculation, target phase determination, phase interval mapping, and amplitude value solution step by step. It does not rely on dedicated hardware devices for signal generation. Digital signal generation can be achieved through procedural calculations, thereby reducing hardware dependence and making it more suitable for miniaturized application scenarios. Attached Figure Description

[0043] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0044] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0045] Figure 2 A flowchart illustrating a method for generating a digital signal according to an embodiment of this application;

[0046] Figure 3 A flowchart illustrating a method for determining the target phase of each sampling point, provided in an embodiment of this application;

[0047] Figure 4 A schematic diagram of an architecture for determining the target phase based on a phase generator, provided for an embodiment of this application;

[0048] Figure 5 A flowchart illustrating a method for determining the phase transition of each sampling point, provided in an embodiment of this application;

[0049] Figure 6 A flowchart illustrating a method for determining the amplitude value of each sampling point of a digital signal, provided in an embodiment of this application;

[0050] Figure 7 A functional block diagram of a sin function calculator provided in this application embodiment;

[0051] Figure 8 A functional block diagram of a cosine function calculator provided in this application embodiment;

[0052] Figure 9 A schematic diagram of a digital signal processing architecture provided in an embodiment of this application;

[0053] Figure 10 A schematic diagram of the structure of a digital signal generation device provided in this application;

[0054] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0055] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0056] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0057] In the field of digital communications, the generation of digital signals is a crucial technical step in ensuring normal communication operation and achieving efficient data transmission. Among various digital signals, chirp signals, for example, are widely used in radar detection, satellite communications, and deep space communications due to their unique advantages such as linear frequency variation over time, controllable bandwidth, and strong resistance to multipath interference.

[0058] Compared to single-tone signals, which only contain information in a fixed frequency dimension, chirp signals can simultaneously carry two-dimensional time-frequency variation characteristics in both time and frequency dimensions. Because of this multi-dimensional time-frequency characterization capability, chirp signals, after transmission through a wireless channel, can sensitively reflect the time-varying fading and frequency-selective fading characteristics of the wireless channel, thus achieving excellent anti-interference capabilities and processing gain. For example, in narrowband satellite mobile communication systems, by introducing chirp signals into the Frequency Correction Channel (FCCH), and leveraging their excellent time-frequency coupling characteristics, high-precision uplink and downlink time-frequency synchronization of the communication link can be reliably achieved.

[0059] Chirp signals, also known as linear frequency modulation (LFM) or linear frequency sweep (LFS) signals, are typically expressed in complex form as shown in the following formula (1):

[0060]

[0061] in, Indicates signal amplitude; This represents waveform parameters and can also be called the sweep frequency. Indicates the frequency sweep period; Indicates the initial phase; This represents the Chirp signal at time t.

[0062] exist from Change to During that time period, the signal will sweep across The frequency range corresponds to a sweep signal bandwidth of . .

[0063] When a receiver uses chirp signals for signal processing services such as channel estimation, time-frequency synchronization, or target detection, it typically needs to generate a reference chirp signal locally for the backend to perform matched filtering and related operations. For digital receivers, a sampled chirp sequence is required for subsequent processing. Assume the receiver's operating sampling frequency is... For a period of If the Chirp signal is sampled in the time domain, then the number of sampling points contained in a single signal period is... satisfy Chirp sequence It can be shown in the following formula (2):

[0064]

[0065] in, This represents the nth sampling point; The sampling period is equal to .

[0066] To obtain the Chirp sequence The various values ​​of are usually solved directly using numerical methods, which require performing squaring operations one by one. Real number multiplication operations Real number addition and complex exponential nonlinear mapping The computation involves multiple complex steps, resulting in a significant overall computational cost, especially for complex exponential mappings. It involves nonlinear function operations, which are highly complex to implement in hardware, making it a major technical challenge in engineering implementation.

[0067] Therefore, the following methods exist in related technologies to achieve high-precision and low-complexity Chirp signal generation.

[0068] One method involves deploying an external digital frequency synthesizer to generate the chirp signal by changing the frequency control word (FCW) in its internal numerically controlled oscillator.

[0069] For example, by utilizing the phase increment characteristics of the Chirp signal, the initial phase and phase increment of the Chirp signal can be calculated by a software program, which then drives the Intellectual Property Core (IP) of DDFS to generate the Chirp signal.

[0070] The DDFS core includes a phase accumulator, waveform memory, digital-to-analog converter (DAC), and low-pass filter. The phase accumulator generates a linear phase accumulation value each clock cycle based on an externally configured frequency control word. This accumulated value is then used to look up the digital amplitude value of the sine wave in the waveform memory, achieving phase-to-amplitude conversion. The DAC converts the output digital amplitude value into a stepped analog signal, which is then filtered by the low-pass filter to remove high-frequency spurious components, ultimately outputting a smooth sine wave, which is the generated chirp signal.

[0071] Another method involves deploying a phase-locked loop (PLL) and using a linearly varying voltage, such as a triangular wave or sawtooth wave, to drive a voltage-controlled oscillator (VCO) within the loop. This linearly modulates the output frequency, thereby generating a chirp signal.

[0072] For example, a triangular wave signal can be used to drive a VCO to output a linearly varying sine wave, thus achieving the output of a chirp signal waveform. Alternatively, a linearly ramped control voltage can be used to drive the VCO to generate an initial chirp signal, which can then be multiplied by a frequency multiplier to generate a higher-frequency signal.

[0073] For example, a digital microprocessor can be used to control the bias voltage of the VCO, thereby generating a chirp signal. In the basic PLL loop structure, in addition to controlling the input voltage of the VCO to modulate the frequency of the output signal, a frequency divider can be introduced to achieve discrete linear variation of the PLL output signal frequency.

[0074] For example, a high-linearity frequency-modulated continuous wave height measurement component is used. Its sweep frequency circuit employs a phase-locked loop (PLL) frequency modulation circuit with frequency adjustment function, mainly composed of a reference clock source, a loop filter, a voltage-controlled oscillator (VCO), a frequency divider, and a fractional-to-frequency synthesizer. The signal path, consisting of the reference clock source, fractional-to-frequency synthesizer, loop filter, and VCO, generates a sinusoidal signal with a preset carrier frequency. The output sinusoidal signal is then processed collaboratively by the frequency divider and fractional-to-frequency synthesizer to ensure that the loop output frequency varies linearly within the loop bandwidth, ultimately generating the chirp signal.

[0075] However, for terminals requiring low cost, miniaturization, and low power consumption, deploying DDFS or PLL significantly increases hardware design complexity, leading to high hardware resource consumption and a large on-chip footprint. Therefore, in application scenarios sensitive to cost, power consumption, and chip area, these solutions relying on dedicated hardware architectures have excessively high hardware investment costs and cannot meet the actual usage needs of miniaturized, low-power terminals.

[0076] Therefore, addressing the aforementioned problems in related technologies, this application proposes a digital signal generation concept that abandons the reliance on dedicated hardware devices for signal generation and instead achieves digital signal generation through an algorithmic processing flow. Specifically, sampling information is acquired, and the phase increment corresponding to each sampling point of the digital signal is calculated based on the sampling information. The target phase of each sampling point within a first interval is determined using the phase increment. Then, the target phase of the first interval is mapped to a second interval with a smaller value range through a preset phase conversion relationship to obtain the converted phase. Finally, the corresponding amplitude value is calculated based on the converted phase of each sampling point to generate the digital signal. This eliminates the need for additional dedicated hardware modules such as DDFS or PLL, effectively reducing hardware design complexity and chip area occupation, and thus better adapting to the practical application requirements of low-cost, miniaturized, and low-power terminals.

[0077] To facilitate understanding of the method in this application, an exemplary application scenario is provided below. Please refer to [link / reference]. Figure 1 , Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application. The application scenario may include terminal 01 and satellite 02.

[0078] Among them, terminal 01 is a digital communication terminal with low cost, miniaturization and low power consumption characteristics, which can be applied to satellite mobile communication scenarios. Terminal 01 needs to generate Chirp signal based on the method in this application for long-distance communication with satellite 02, so as to complete key communication processes such as time and frequency synchronization and channel estimation, so as to ensure the stability and transmission quality of the communication link with satellite 02.

[0079] It is understood that the above examples are for illustrative purposes only and do not limit this application. The specific details can be determined based on the actual application situation.

[0080] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0081] Please see Figure 2 , Figure 2 This is a flowchart illustrating a method for generating a digital signal according to an embodiment of this application. The execution entity of this method can be a digital signal generating device. This digital signal generating device can be implemented through a computer program, or through a medium storing the relevant computer program, such as a USB flash drive and / or optical disc, or through a physical device integrating or installing the relevant computer program, such as a chip or electronic device. The electronic device can be a smart terminal or a server. Figure 2 As shown, the method may include the following steps:

[0082] S201. Obtain sampling information.

[0083] Optionally, the sampling information includes, but is not limited to: waveform parameters Frequency sweep cycle Sampling parameters and the number of sampling points .

[0084] The above sampling information can be pre-configured and obtained according to actual communication needs.

[0085] S202. Determine the phase increment of each sampling point of the digital signal based on the sampling information.

[0086] One possible implementation is to determine the first parameter of the nth sampling point based on the waveform parameters and the sampling parameters, for the nth sampling point. , This represents the number of sampling points.

[0087] For each sampling point of the digital signal, they are processed sequentially. For the nth sampling point, based on the acquired waveform parameters and sampling parameters, the first parameter of the nth sampling point is determined by a preset calculation strategy. The first parameter can reflect the influence of the waveform parameters on the phase.

[0088] Alternatively, the first parameter can be determined by the following formula (3):

[0089]

[0090] Based on the sampling parameters, the sweep period, and the nth sampling point, the second parameter of the nth sampling point is determined. The second parameter can reflect the dynamic adjustment of the phase by the sweep period.

[0091] Based on the sampling parameters, the scanning period, and the index of the nth sampling point, the second parameter of the nth sampling point is determined through a preset calculation strategy.

[0092] Alternatively, the second parameter can be determined using the following formula (4):

[0093]

[0094] in, Represent a Total number of sampling points within, .

[0095] The first parameter is multiplied by the second parameter, and the result of the multiplication is determined as the phase increment of the nth sampling point, ensuring that the phase calculation is consistent with the frequency sweep characteristics.

[0096] Alternatively, the phase increment of the nth sampling point can be determined by the following formula (5):

[0097]

[0098] S203. Determine the target phase of each sampling point based on the phase increment of each sampling point. The range of the target phase is in the first interval.

[0099] Based on the phase increment at each sampling point, using the phase 2 The target phase of each sampling point is determined periodically. The target phase can also be called the normalized phase. The value range corresponding to the first interval is... .

[0100] S204. Based on the pre-configured phase conversion relationship, determine the conversion phase corresponding to the target phase of each sampling point mapped to the second interval. The value range of the second interval is smaller than that of the first interval.

[0101] In this embodiment, a phase transformation relationship is pre-configured based on the periodicity of trigonometric functions to implement a mapping rule for phase interval compression.

[0102] Based on this mapping rule, the target phase of each sampling point in the first interval is mapped one by one to the second interval with a smaller value range, so as to obtain the transformed phase corresponding to each sampling point. The complexity of subsequent phase operations can be reduced by interval compression.

[0103] Optionally, the range of values ​​for the second corresponding value can be... .

[0104] S205. Based on the conversion phase of each sampling point, determine the amplitude value of each sampling point of the digital signal to generate the digital signal.

[0105] Based on the correspondence between the conversion phase and the amplitude value, the conversion phase of each sampling point is processed to obtain the amplitude value corresponding to each sampling point. The amplitude values ​​of each sampling point are arranged according to the sampling time sequence to complete the generation of the digital signal.

[0106] In the above embodiments of this application, by acquiring sampling information, the phase increment of each sampling point of the digital signal is determined one by one based on the acquired sampling information, and the target phase of each sampling point is determined sequentially using the phase increment corresponding to each sampling point. Then, according to the pre-configured phase conversion relationship, the target phase of each sampling point in the first interval is mapped to a second interval with a smaller value range to obtain the corresponding converted phase. Based on the converted phase of each sampling point, the amplitude value of the digital signal corresponding to each sampling point is determined, thus completing the generation of the digital signal. This application realizes signal generation through procedural calculations, without relying on dedicated hardware modules such as DDFS and PLL. It calculates the phase increment, target phase, converted phase, and amplitude value step by step through the sampling information to form a complete signal generation chain. This method replaces hardware modules with mathematical operations, significantly reducing hardware resource consumption and design complexity, thereby adapting to the application requirements of low-cost, miniaturized terminal devices.

[0107] Furthermore, based on the above embodiments, the following embodiments illustrate the application of phase increments at each sampling point. Determine the target phase of each sampling point The process can be specifically determined by the phase generator configured in the terminal.

[0108] Please see Figure 3 , Figure 3 This application provides a flowchart illustrating a method for determining the target phase of each sampling point, which may include the following steps:

[0109] S301. Determine the initial phase of the first sampling point based on the waveform parameters, sweep period, and sampling parameters.

[0110] The following will combine Figure 4 For a description of the content in this embodiment, please refer to [link / reference]. Figure 4 , Figure 4 This is a schematic diagram of an architecture for determining the target phase based on a phase generator, provided in an embodiment of this application.

[0111] like Figure 4 As shown, based on the input parameters, namely the obtained waveform parameters, scanning period, and sampling parameters, the initial phase of the first sampling point is determined by a preset calculation formula. initial phase of time The initial phase is the phase reference at the start of sampling of the digital signal.

[0112] Alternatively, the initial phase of the first sampling point can be determined by the following formula (6). :

[0113]

[0114] Specifically, the phase generator is based on waveform parameters Frequency sweep cycle Sampling parameters Sure To simplify calculations, the following constants can be calculated first. And keep that amount from being released.

[0115] It can be determined by the following formula (7). :

[0116]

[0117] If the phase generator uses the sampling period Replace sampling parameters As input, division operations can be avoided, and the constant can be used in this way. for , Phase calculations can be pre-calculated and stored in the phase generator, avoiding redundant calculations and thus improving computational efficiency.

[0118] therefore, The calculation expression is shown in the following formula (8):

[0119]

[0120] in, 2 indicates a right shift operation of 2 bits. This operation can replace division, reducing computational complexity and making it suitable for low-power scenarios.

[0121] S302. Perform a modulo operation based on the initial phase of the first sampling point to obtain the target phase of the first sampling point.

[0122] Alternatively, the initial phase can be modulo-operated using the following formula (9) to determine the first phase. The modulo operation result of each sampling point is the target phase. .

[0123]

[0124] S303. Perform iterative calculations based on the target phase of the first sampling point and the phase increment of each sampling point to determine the target phase of each sampling point.

[0125] Based on the initial phase of the first sampling point, iterative calculations are performed using the phase increments of each sampling point. That is, the phase of each sampling point is the sum of the target phase obtained by modulo operation of the previous sampling point and the corresponding phase increment of the current sampling point. This process continues until all sampling points have been calculated. Through this iterative operation, the target phase of each sampling point can be obtained.

[0126] One possible implementation is to assume that the first phase of the nth sampling point has been calculated by summing the target phase after modulo operation at the (n-1)th sampling point and the phase increment corresponding to the nth sampling point. Then, the modulo operation result of the nth sampling point, i.e., the target phase, is determined according to the following formula (10). :

[0127]

[0128] Specifically, the phase generator is based on the phase 2 Periodic pairs Normalization is performed to obtain the target phase. To simplify the calculation, constants can be configured first. .

[0129] The calculation expression is shown in the following formula (11):

[0130]

[0131] in, This indicates rounding down to the nearest integer.

[0132] After determining the target phase of the nth sampling point, the current sampling point to be calculated is then determined based on the target phase. One sampling point.

[0133] Specifically, according to the first The target phase of the sampling point and the first Phase increment corresponding to each sampling point Determine the first The first phase of each sampling point.

[0134] The number can be determined by the following formula (12). The first phase of each sampling point:

[0135]

[0136] Specifically, to simplify calculations, the phase generator can first calculate a constant. And keep the variable from being released.

[0137] The calculation expression is shown in the following formula (13):

[0138]

[0139] The phase increment is calculated as follows (14).

[0140]

[0141] in, This indicates a left shift operation of 2 bits.

[0142] For the first The first phase of the sampling point is modulo-operated to obtain the first... The target phase of the sampling point, the modulus value of the modulo operation matches the value range of the first interval, thus allowing the target phase of the sampling point to be sampled. The target phase specification of each sampling point is... .

[0143] Then repeat the above steps, that is, first determine the first phase of the current sampling point based on the target phase of the previous sampling point and the phase increment corresponding to the current sampling point to be calculated, then perform a modulo operation on the first phase to determine the target phase of the current sampling point to be calculated, until all sampling points are calculated, thereby obtaining the target phase of each sampling point, ensuring that all target phases fall within the preset first interval.

[0144] By constraining the phase values ​​of each sampling point to Within the range, ensuring the periodicity of the target phase can reduce signal distortion caused by phase overflow.

[0145] Then, based on the sampling order of each sampling point and the target phase corresponding to each sampling point, the target phase sequence is output.

[0146] In the above embodiments of this application, the initial phase of the first sampling point is accurately determined by combining waveform parameters, frequency sweep period, and sampling parameters, providing a precise benchmark for the phase calculation of subsequent sampling points and effectively reducing the digital signal waveform distortion problem caused by initial phase deviation. The initial phase of the first sampling point is modulo-operated to obtain the target phase of the first sampling point. Then, starting from this target phase, iterative calculations are performed using the phase increments of each sampling point to sequentially calculate the target phases of all sampling points. The computational logic is simple and easy to implement through algorithms, requiring no dedicated hardware assistance, significantly reducing the hardware overhead and design complexity of phase calculation. Phase modulo constraints are completed throughout the iterative process, ensuring that the target phases of all sampling points are stably limited within a predetermined range, guaranteeing the consistency and standardization of the target phases. This lays a reliable foundation for subsequent phase conversion and amplitude calculation, further improving the accuracy and stability of digital signal generation, meeting the application requirements of low-cost, miniaturized, and low-power terminals.

[0147] Based on any of the above embodiments, the following examples illustrate the process of determining the target phase of each sampling point to be mapped to the corresponding conversion phase of the second interval according to a pre-configured phase conversion relationship.

[0148] Please see Figure 5 , Figure 5 This application provides a flowchart illustrating a method for determining the phase transition of each sampling point, which may include the following steps:

[0149] S501. Based on the target phase of each sampling point, match within multiple sub-intervals to determine the target sub-interval where each sampling point is located.

[0150] In this embodiment, an angle converter can be used to... Trigonometric functions within an interval and Calculation conversion to Within the interval, to reduce the amount of calculation.

[0151] Optionally, you can first... Transformation of trigonometric function calculations to Within the range.

[0152] Specifically, it can be shown in the following formulas (15) and (16):

[0153]

[0154]

[0155] Then The trigonometric function calculation can be converted to Within the interval, as shown in formulas (17) and (18).

[0156]

[0157]

[0158] In this embodiment, it is also possible to directly use Transformation of trigonometric function calculations to Within the interval, without needing to pass through This intermediate step.

[0159] Based on the above, the phase conversion relationship is pre-configured in this embodiment, as shown in Table 1 below:

[0160] Table 1

[0161]

[0162] In Table 1, the high-order bits refer to the floating-point phase that is converted into a fixed-point integer according to the number of bits specified by the hardware / algorithm during the pre-configuration process. After quantization, a multi-bit fixed-point number is obtained. Only the highest 3 bits are extracted and used as the address index of the lookup table to find the corresponding phase mapping value, trigonometric function approximation value, or amplitude value, which greatly simplifies the calculation and reduces storage resources.

[0163] As shown in Table 1, the interval range corresponding to the phase transformation relationship is the value range of the first interval, i.e. The first interval is divided into the aforementioned multiple sub-intervals, namely... Each interval has a corresponding mapping relationship between the target phase and the conversion phase.

[0164] Therefore, based on the above configuration, the calculation relationship selector matches the target phase of each sampling point in multiple sub-intervals to determine the target sub-interval where the target phase is located.

[0165] S502. Based on the mapping relationship between the target phase and the conversion phase in the target sub-interval where each sampling point is located, determine the conversion phase corresponding to the target phase of each sampling point, and the range of values ​​of the conversion phase corresponding to the second interval.

[0166] Then, based on the mapping relationship between the target phase and the conversion phase in the target sub-interval in Table 1, the conversion phase corresponding to the target phase is obtained by querying, thereby ensuring that the conversion phase of each sampling point is in the second interval with a value range smaller than that of the first interval.

[0167] Based on the symmetry of trigonometric functions, the phase values ​​in the first interval can be mapped to the second interval through symmetry, thereby reducing the amount of computation. This selection strategy ensures that all trigonometric function values ​​are still covered after interval compression, but the computational complexity is significantly reduced.

[0168] In the above embodiments of this application, the target phase of each sampling point is matched to the corresponding target sub-interval, and the transformed phase mapped to the second interval is obtained by using the preset mapping relationship of the sub-interval. This interval division and segmented mapping method can achieve accurate convergence of the transformed phase from a large range of target phases to a smaller range of values, thereby effectively compressing the scale of the phase operation interval and simplifying the computational workload of subsequent trigonometric function solving and amplitude conversion. Furthermore, while ensuring the accuracy of phase mapping, it significantly reduces storage resources and computational overhead, so as to adapt to the engineering implementation conditions of low-power, small-area, and low-cost terminals, and ensure the regularity and consistency of the digital signal generated waveform.

[0169] Furthermore, based on any of the above embodiments, the following examples illustrate the process of determining the amplitude value of each sampling point of the digital signal according to the conversion phase of each sampling point.

[0170] Please see Figure 6 , Figure 6 This application provides a flowchart illustrating a method for determining the amplitude value of each sampling point of a digital signal. The method may include the following steps:

[0171] S601. Determine the trigonometric function of each sampling point based on the transformation phase of each sampling point.

[0172] For the transformation phase of each sampling point, determine the trigonometric function corresponding to that transformation phase. and .

[0173] S602. Based on a preset approximation algorithm, the trigonometric functions of each sampling point are solved to determine the approximate values ​​of the trigonometric functions of each sampling point.

[0174] This approximation algorithm is a simplified algorithm that can reduce the complexity of solving trigonometric functions. It obtains approximate values ​​of trigonometric functions at each sampling point, reducing computational overhead while ensuring computational accuracy.

[0175] In this embodiment, the preset approximation algorithm can be based on the Taylor expansion of trigonometric functions. Trigonometric function values ​​within and .

[0176] and exist The value on, used in The Taylor expansion at the given location is used for approximate calculation, as shown in the following formulas (19) and (20):

[0177]

[0178]

[0179] Specifically, a trigonometric calculator can be used to perform the operation on... Trigonometric function values ​​within the interval , Approximate calculation.

[0180] Please see Figure 7 , Figure 7 A functional block diagram of a sin function calculator provided in this application embodiment is shown below. Figure 7 As shown, The calculation method can be shown in the following formulas (21)-(22):

[0181]

[0182]

[0183] in, Indicates the phase parameter; This indicates a right shift operation of 3 bits.

[0184] Please see Figure 8 , Figure 8 A functional block diagram of a cosine function calculator provided in this application embodiment is shown below. Figure 8 As shown, The calculation method can be shown in the following formula (23):

[0185]

[0186] in, This indicates a right shift operation of 4 bits.

[0187] S603. Determine the amplitude value of each sampling point of the digital signal based on the approximate trigonometric function values ​​of each sampling point.

[0188] By combining approximate values ​​to calculate complex amplitude values, the continuity and accuracy of signal waveforms are ensured, making it suitable for low-power scenarios.

[0189] The approximate trigonometric function values ​​of each sampling point are input into the preset waveform generation algorithm of the digital signal to obtain the output results of each sampling point. The output results of each sampling point are then determined as the amplitude values ​​of each sampling point of the digital signal.

[0190] In this embodiment, according to Euler's formula The preset waveform generation algorithm can be used to generate the waveform amplitude value of the Chirp digital signal. The preset waveform generation algorithm converts the approximate values ​​of trigonometric functions into complex amplitude values ​​based on Euler's formula, generating the time-domain representation of the Chirp signal.

[0191] Specifically, it can be shown in the following formula (24):

[0192]

[0193] Specifically, by using a waveform combiner, based on the above formula, the conversion relationship between angles in Table 1, and the approximate trigonometric function values ​​determined in the above steps, the amplitude values ​​of each sampling point of the digital signal can be determined.

[0194] In the above embodiments of this application, for each sampling point's transformed phase, a corresponding trigonometric function expression is determined, and a preset approximation algorithm is used to solve the trigonometric functions to obtain approximate values. These approximate values ​​are then used to calculate the signal amplitude value corresponding to each sampling point. By solving the trigonometric functions corresponding to the transformed phase of each sampling point, calculations can be performed using a compressed phase interval, thereby significantly reducing the computational range and overhead of trigonometric function solving, and lowering the algorithm's implementation complexity and hardware resource consumption.

[0195] To facilitate understanding of the method of this application, based on the above-described embodiments, through... Figure 9 For a brief explanation of the working process between the phase generator, angle converter, trigonometric function calculator, calculation relation selector, and waveform combiner, please refer to [link to relevant documentation]. Figure 9 , Figure 9 This is a schematic diagram of a digital signal processing architecture provided in an embodiment of this application.

[0196] The phase generator determines the phase increment of each sampling point of the digital signal based on the sampling information, and determines the target phase of each sampling point based on the phase increment of each sampling point.

[0197] The angle converter determines the conversion phase corresponding to the second interval for each sampling point target phase based on the pre-configured phase conversion relationship.

[0198] The trigonometric function calculator uses a preset approximation algorithm to solve the trigonometric functions at each sampling point and determine the approximate values ​​of the trigonometric functions at each sampling point.

[0199] The calculation relationship selector matches in multiple sub-intervals based on the target phase of each sampling point to determine the target sub-interval where each sampling point is located, so as to determine the conversion phase corresponding to the target phase of each sampling point based on the target sub-interval.

[0200] The waveform combiner determines the amplitude value of each sampling point of the digital signal based on the conversion phase of each sampling point, so as to generate and output the digital signal, i.e., the waveform.

[0201] The specific implementation process of each step has been described in detail in the above embodiments. Please refer to the above embodiments for details. To avoid redundancy, it will not be repeated here.

[0202] Among related technologies, there is also a method for generating chirp signals by mapping phase to amplitude based on trigonometric function lookup tables. This method determines the actual phase value by accumulating phase increments, then narrows the lookup range of the trigonometric function's independent variable based on the mapping relationship between the phase interval and the trigonometric function table to save storage space. Finally, the transformed phase is used to look up the corresponding trigonometric function table to complete the mapping from phase value to waveform amplitude value, thus generating the complex amplitude value of the chirp sequence.

[0203] In the process of mapping phase to amplitude by looking up a table, a large sin / cos table is often required to ensure the accuracy of the output waveform. However, this will occupy a lot of storage space. Larger storage space means larger device area and power consumption, which is not suitable for miniaturized application scenarios.

[0204] In this application, the overall phase interval is divided into multiple sub-intervals and a mapping relationship is pre-established. The target phase is mapped to a smaller second interval to obtain the transformed phase. The symmetry of trigonometric functions is used to reduce the amount of computation. The transformed phase is matched with the corresponding trigonometric functions, and the approximate values ​​of the trigonometric functions are solved through a preset approximation algorithm to determine the amplitude value of each sampling point. Although this application also configures a mapping table, it only needs to adapt to the small-scale mapping relationship of the compressed smaller phase interval. There is no need to configure a large-capacity trigonometric function lookup table covering the entire phase range, which greatly reduces storage resource consumption, effectively reduces the device footprint and operating power consumption, and is more suitable for miniaturized and low-power application scenarios.

[0205] This application also provides a digital signal generation apparatus, please refer to [link to relevant documentation]. Figure 10 , Figure 10 A schematic diagram of a digital signal generation device provided in this application is shown below. Figure 10 As shown, the apparatus provided in this embodiment includes:

[0206] The acquisition module 1001 is used to acquire sampling information.

[0207] The determination module 1002 is used to determine the phase increment of each sampling point of the digital signal based on the sampling information.

[0208] The determination module 1002 is also used to determine the target phase of each sampling point based on the phase increment of each sampling point, and the range of the target phase is in the first interval.

[0209] The determining module 1002 is also used to determine the conversion phase corresponding to the target phase of each sampling point mapped to the second interval according to the pre-configured phase conversion relationship, wherein the value range of the second interval is smaller than that of the first interval.

[0210] The determination module 1002 is also used to determine the amplitude value of each sampling point of the digital signal based on the conversion phase of each sampling point, so as to generate the digital signal.

[0211] In one possible implementation, the sampling information includes: waveform parameters, sweep period, sampling parameters, and number of sampling points. Based on the sampling information, the phase increment of each sampling point of the digital signal is determined. The determination module 1002 is specifically used for:

[0212] For the nth sampling point, the first parameter of the nth sampling point is determined based on the waveform parameters and the sampling parameters. , This represents the number of sampling points.

[0213] The second parameter of the nth sampling point is determined based on the sampling parameters, the sweep period, and the nth sampling point.

[0214] Multiply the first parameter by the second parameter, and determine the result of the multiplication as the phase increment of the nth sampling point.

[0215] In one possible implementation, module 1002 is specifically used for:

[0216] The initial phase of the first sampling point is determined based on the waveform parameters, the sweep period, and the sampling parameters.

[0217] The initial phase of the first sampling point is moduloed to obtain the target phase of the first sampling point.

[0218] The target phase of each sampling point is determined by iterative calculation based on the target phase of the first sampling point and the phase increment of each sampling point.

[0219] In one possible implementation, the interval range corresponding to the phase transformation relationship is the value range of the first interval. The first interval is divided into multiple sub-intervals, and each sub-interval corresponds to a mapping relationship between the target phase and the transformed phase. The determining module 1002 is specifically used for:

[0220] Based on the target phase of each sampling point, matching is performed in multiple sub-intervals to determine the target sub-interval where each sampling point is located.

[0221] Based on the mapping relationship between the target phase and the transformed phase in the target sub-interval where each sampling point is located, the transformed phase corresponding to the target phase of each sampling point is determined, and the value range of the transformed phase in the second interval is determined.

[0222] In one possible implementation, module 1002 is specifically used for:

[0223] The trigonometric function of each sampling point is determined based on the transformation phase of each sampling point.

[0224] The trigonometric functions of each sampling point are solved based on a preset approximation algorithm to determine the approximate values ​​of the trigonometric functions at each sampling point.

[0225] The amplitude value of each sampling point of the digital signal is determined based on the approximate trigonometric function values ​​of each sampling point.

[0226] In one possible implementation, module 1002 is specifically used for:

[0227] The approximate trigonometric function values ​​of each sampling point are input into the preset waveform generation algorithm of the digital signal to obtain the output results of each sampling point.

[0228] The output results of each sampling point are determined as the amplitude value of each sampling point of the digital signal.

[0229] The digital signal generation device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0230] This application also provides an electronic device, please refer to [link to application]. Figure 11 , Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 11 As shown, the electronic device provided in this embodiment includes at least one processor 1101 and a memory 1102. Optionally, the device 110 also includes a communication component 1103. The processor 1101, memory 1102, and communication component 1103 are connected via a bus 1104.

[0231] In a specific implementation, at least one processor 1101 executes computer execution instructions stored in memory 1102, causing at least one processor 1101 to perform the above-described method.

[0232] The specific implementation process of processor 1101 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0233] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0234] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0235] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0236] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0237] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0238] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0239] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0240] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0241] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0242] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0243] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0244] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0245] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for generating a digital signal, characterized in that, include: Obtain sampling information; The phase increment of each sampling point of the digital signal is determined based on the sampling information. The target phase of each sampling point is determined based on the phase increment of each sampling point, and the range of the target phase is in the first interval; Based on the pre-configured phase conversion relationship, the conversion phase corresponding to the target phase of each sampling point mapped to the second interval is determined, and the value range of the second interval is smaller than that of the first interval; The amplitude value of each sampling point of the digital signal is determined based on the conversion phase of each sampling point in order to generate the digital signal.

2. The method according to claim 1, characterized in that, The sampling information includes: waveform parameters, sweep period, sampling parameters, and number of sampling points. Determining the phase increment of each sampling point of the digital signal based on the sampling information includes: For the nth sampling point, the first parameter of the nth sampling point is determined based on the waveform parameters and the sampling parameters. , The number of sampling points; The second parameter of the nth sampling point is determined based on the sampling parameters, the frequency sweep period, and the nth sampling point. The first parameter is multiplied by the second parameter, and the result of the multiplication is determined as the phase increment of the nth sampling point.

3. The method according to claim 2, characterized in that, The step of determining the target phase of each sampling point based on the phase increment of each sampling point includes: The initial phase of the first sampling point is determined based on the waveform parameters, the frequency sweep period, and the sampling parameters. Perform a modulo operation on the initial phase of the first sampling point to obtain the target phase of the first sampling point; The target phase of each sampling point is determined by iterative calculation based on the target phase of the first sampling point and the phase increment of each sampling point.

4. The method according to any one of claims 1-3, characterized in that, The interval range corresponding to the phase conversion relationship is the value range of the first interval. The first interval is divided into multiple sub-intervals, and each sub-interval corresponds to a mapping relationship between the target phase and the conversion phase. The step of determining the target phase mapping of each sampling point to the corresponding transformed phase of the second interval according to the pre-configured phase transformation relationship includes: Based on the target phase of each sampling point, matching is performed in the multiple sub-intervals to determine the target sub-interval where each sampling point is located. Based on the mapping relationship between the target phase and the transformed phase in the target sub-interval where each sampling point is located, the transformed phase corresponding to the target phase of each sampling point is determined, and the transformed phase corresponds to the value range of the second interval.

5. The method according to claim 4, characterized in that, The step of determining the amplitude value of each sampling point of the digital signal based on the conversion phase of each sampling point includes: The trigonometric function of each sampling point is determined based on the transformation phase of each sampling point. The trigonometric functions of each sampling point are solved based on a preset approximation algorithm to determine the approximate values ​​of the trigonometric functions of each sampling point. The amplitude value of each sampling point of the digital signal is determined based on the approximate trigonometric function values ​​of each sampling point.

6. The method according to claim 5, characterized in that, The step of determining the amplitude value of each sampling point of the digital signal based on the trigonometric function approximation value of each sampling point includes: The approximate trigonometric function values ​​of each sampling point are input into the preset waveform generation algorithm of the digital signal to obtain the output results of each sampling point; The output results of each sampling point are determined as the amplitude value of each sampling point of the digital signal.

7. A digital signal generation apparatus, characterized in that, include: The acquisition module is used to acquire sampling information; The determination module is used to determine the phase increment of each sampling point of the digital signal based on the sampling information; The determining module is further configured to determine the target phase of each sampling point based on the phase increment of each sampling point, wherein the range of the target phase is in the first interval; The determining module is further configured to determine the transformation phase corresponding to the target phase of each sampling point mapped to the second interval according to the pre-configured phase transformation relationship, wherein the value range of the second interval is smaller than that of the first interval; The determining module is further configured to determine the amplitude value of each sampling point of the digital signal based on the conversion phase of each sampling point, so as to generate the digital signal.

8. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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