Multi-channel signal acquisition and calculation method, device and equipment

Abstract

The invention relates to the technical field of signal processing, and discloses a multichannel signal acquisition and calculation method, device and equipment. The method is applied to a multichannel signal acquisition and calculation device, the device comprises an acquisition card, a CPU and a GPU, the method is executed by the GPU, and the method comprises the following steps: firstly, receiving a satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and is sent to the CPU; then, the satellite baseband signal is segmented to each sub-channel; and finally, through each thread block in the GPU, based on the non-uniform digital channelization parameter corresponding to each sub-channel, performing non-uniform digital channelization processing on the satellite baseband signal in each sub-channel to obtain a satellite narrowband signal corresponding to each sub-channel. And the satellite narrowband signal is sent to the CPU for realizing satellite positioning. According to the scheme, the occupied space is saved, the signal transmission rate is improved, and the signal processing efficiency and real-time performance are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and particularly to a multi-channel signal acquisition and calculation method, device, and equipment. Background Art

[0002] In a satellite positioning system, the intermediate frequency signal obtained after down-converting the radio frequency signal transmitted by a satellite is crucial for subsequent positioning.

[0003] In the related art, an acquisition, storage, and preprocessing device is used to acquire the intermediate frequency analog signal. The acquisition card in the acquisition, storage, and preprocessing device realizes the conversion of the analog signal to a digital signal, and completes digital down-conversion to obtain the target baseband signal. Then, when the GPU parameter estimation device is called, a time-frequency difference parameter estimation algorithm is used to obtain the time difference DTO and frequency difference DFO results of the target radiation source for subsequent positioning.

[0004] However, in the above solution, the acquisition, storage, and preprocessing device and the GPU parameter estimation device are two discrete devices, which occupy a large space. Moreover, the signal acquisition and calculation process involves data transmission between the two discrete devices, which requires high transmission efficiency and low error rate. Due to the large amount of data, there are also high requirements for the storage capacity and real-time processing ability of the backend GPU parameter estimation device, resulting in a high implementation threshold and relatively low data processing efficiency. Summary of the Invention

[0005] In view of this, an object of the present invention is to provide a multi-channel signal acquisition and calculation method, device, and equipment to solve the problems of large space occupation of devices and relatively low data processing efficiency in signal acquisition and calculation in the related art.

[0006] In a first aspect, the present invention provides a multi-channel signal acquisition and calculation method. The method is applied to a multi-channel signal acquisition and calculation device, which includes an acquisition card, a CPU, and a GPU. The method is executed by the GPU, and the method includes:

[0007] Receiving the satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and sent to the CPU;

[0008] Dividing the satellite baseband signal into each sub-channel;

[0009] Based on the non-uniform digital channelization parameters corresponding to each sub-channel, through each thread block in the GPU, performing non-uniform digital channelization processing on the satellite baseband signal in each sub-channel to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning.

[0010] In an optional implementation manner, the method further includes:

[0011] Receive the bandwidth and center frequency of each sub-channel sent by the CPU;

[0012] According to the bandwidth and center frequency of each sub-channel, divide the satellite baseband signal into each sub-channel to obtain the satellite baseband signal corresponding to each sub-channel.

[0013] In an alternative embodiment, the non-uniform digital channelization parameters include a mixing phase factor, a low-pass filter coefficient, and a decimation factor; wherein, each sub-channel corresponds to different mixing phase factors, low-pass filter coefficients, and decimation factors;

[0014] The method further includes:

[0015] Load the mixing phase factor, low-pass filter coefficient, and decimation factor corresponding to each sub-channel into the corresponding thread block, and perform digital down-conversion and decimation processing on the satellite baseband signal of each sub-channel by each thread block based on the corresponding mixing phase factor, low-pass filter coefficient, and decimation factor to obtain the satellite narrowband signal corresponding to each sub-channel.

[0016] In a second aspect, the present invention provides a multi-channel signal acquisition and calculation device, which is applied to a multi-channel signal acquisition and calculation device. The device includes an acquisition card, a CPU, and a GPU. The device is set in the GPU. The device includes:

[0017] A receiving module, configured to receive the satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and sent to the CPU;

[0018] A splitting module, configured to split the satellite baseband signal into each sub-channel;

[0019] A processing module, configured to perform non-uniform digital channelization processing on the satellite baseband signal in each sub-channel through each thread block in the GPU based on the non-uniform digital channelization parameters corresponding to each sub-channel respectively to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning.

[0020] In a third aspect, the present invention provides a multi-channel signal acquisition and calculation device, including:

[0021] An acquisition card, configured to acquire a satellite baseband signal;

[0022] A CPU, communicatively connected to the acquisition card, configured to receive the satellite baseband signal sent by the acquisition card;

[0023] A GPU, communicatively connected to the CPU, is configured to receive the satellite baseband signal sent by the CPU, split the satellite baseband signal into each sub-channel, and perform non-uniform digital channelization processing on the satellite baseband signal in each sub-channel through each thread block in the GPU based on the non-uniform digital channelization parameters respectively corresponding to each sub-channel, so as to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning.

[0024] In an alternative embodiment, each of the thread blocks forms a two-dimensional grid; the number of thread blocks included in the Y dimension of the two-dimensional grid is determined based on the number of sub-channels; the number of thread blocks included in the X dimension of the two-dimensional grid is determined based on the maximum value of the data length of the satellite baseband signal in each sub-channel.

[0025] In an alternative embodiment, the acquisition card includes:

[0026] Multiple channels of ADC units, configured to collect the satellite intermediate frequency analog signal and perform analog-to-digital conversion to obtain the satellite intermediate frequency signal;

[0027] An FPGA, communicatively connected to the ADC unit, is configured to perform digital down-conversion processing on the satellite intermediate frequency signal to obtain the satellite baseband signal.

[0028] In a fourth aspect, the present invention provides a computer device, including: a memory and a processor, which are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the multi-channel signal acquisition and calculation method according to the first aspect or any corresponding embodiment thereof.

[0029] In a fifth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the multi-channel signal acquisition and calculation method according to the first aspect or any corresponding embodiment thereof.

[0030] In a sixth aspect, the present invention provides a computer program product, including computer instructions, and the computer instructions are used to cause a computer to execute the multi-channel signal acquisition and calculation method according to the first aspect or any corresponding embodiment thereof.

[0031] In a seventh aspect, the present invention provides a satellite positioning system, including:

[0032] A multi-channel signal acquisition and calculation device according to the third aspect or any corresponding embodiment thereof;

[0033] A satellite timekeeping device, configured to send an external clock signal to the multi-channel signal acquisition and calculation device for the multi-channel signal acquisition and calculation device to be frequency-locked and phase-coherent with the satellite positioning system;

[0034] A positioning processing device, communicatively connected to the multi-channel signal acquisition and calculation device, is configured to receive the output result of the multi-channel signal acquisition and calculation device and calculate a satellite positioning result according to the output result.

[0035] The technical solution provided by the present invention may include the following beneficial effects:

[0036] The multi-channel signal acquisition and calculation method provided by the present invention is applied to a multi-channel signal acquisition and calculation device, which includes an acquisition card, a CPU, and a GPU. This method is executed by the GPU. The method first receives a satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and sent to the CPU; then the satellite baseband signal is segmented into each sub-channel; finally, through each thread block in the GPU, based on the non-uniform digital channelization parameters corresponding to each sub-channel, the satellite baseband signal in each sub-channel is subjected to non-uniform digital channelization processing to obtain a satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning. In the above solution, by integrating the acquisition card, CPU, and GPU into a multi-channel signal acquisition and calculation device, the occupied space is saved and the signal transmission rate is improved; by combining the control flow ability of the CPU and the repetitive logical operation ability of the GPU, the satellite baseband signal is segmented into each sub-channel and the segmented satellite baseband signal is processed in parallel by each thread block in the GPU, enabling a large amount of data to be processed simultaneously, and improving the signal processing efficiency and real-time performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 Shows a schematic structural diagram of a satellite positioning system in the related art;

[0039] Figure 2 Is a schematic flowchart of a multi-channel signal acquisition and calculation method according to an embodiment of the present invention;

[0040] Figure 3 Is a schematic flowchart of another multi-channel signal acquisition and calculation method according to an embodiment of the present invention;

[0041] Figure 4 Is a schematic flowchart of the non-uniform digital channelization processing jointly performed by the CPU and the GPU according to an embodiment of the present invention;

[0042] Figure 5 is a schematic structural diagram of a multi-channel signal acquisition and calculation device according to an embodiment of the present invention;

[0043] Figure 6 is a schematic diagram for comparing the structures of a CPU and a GPU according to an embodiment of the present invention;

[0044] Figure 7 is a schematic diagram of a GPU performing digital down-conversion and decimation through each thread block according to an embodiment of the present invention;

[0045] Figure 8 is a schematic flow diagram of an FPGA performing digital down-conversion processing according to an embodiment of the present invention;

[0046] Figure 9 is a schematic flow diagram of an ADC, an FPGA, and a GPU implementing digital channelization according to an embodiment of the present invention;

[0047] Figure 10 is a connection relationship diagram of a multi-channel signal acquisition and calculation device according to an embodiment of the present invention;

[0048] Figure 11 is a motherboard slot sorting diagram of a multi-channel signal acquisition and calculation device according to an embodiment of the present invention;

[0049] Figure 12 is a structural block diagram of a multi-channel signal acquisition and calculation device according to an embodiment of the present invention;

[0050] Figure 13 is a schematic hardware structure diagram of a computer device according to an embodiment of the present invention. Specific embodiments

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0052] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. These are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention. In addition, the terms "first", "second", "third" are only used for descriptive purposes and should not be construed as indicating or implying relative importance.

[0053] In the description of the present invention, it should be noted that unless otherwise clearly specified and defined, the terms "mounted", "connected", "coupled" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0054] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0055] In a satellite positioning system, the intermediate frequency signal obtained by down-converting the radio frequency signal transmitted by a satellite is crucial for subsequent positioning.

[0056] Figure 1 The structural schematic diagram of a satellite positioning system in the related art is shown. In the related art, an acquisition storage preprocessing device is used to acquire the intermediate frequency analog signal. The acquisition card in the acquisition storage preprocessing device realizes the conversion from analog signal to digital signal, and performs digital down-conversion to obtain the target baseband signal. Then, when the GPU parameter estimation device is called, the time difference of arrival (DTO) and the frequency difference of arrival (DFO) results of the target radiation source are obtained by using the time-frequency difference parameter estimation algorithm, so as to provide the results for subsequent positioning processing by the positioning device.

[0057] However, in the above solution, the acquisition storage preprocessing device and the GPU parameter estimation device are usually deployed in a computer room and are two discrete devices, which occupy a large space; the signal acquisition and calculation process involves data transmission between two discrete devices. The amount of satellite baseband signal data output by the acquisition storage preprocessing device is large, and it is necessary to transmit the data to the backend GPU parameter estimation device through a high-speed interface, which requires a high bit error rate for the long-term operation of the transmission link, and also has high requirements for the storage capacity and real-time processing ability of the backend GPU parameter estimation device. The cost is high, the implementation threshold is high, and the data processing efficiency is relatively low.

[0058] According to an embodiment of the present invention, an embodiment of a multi-channel signal acquisition and calculation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0059] In this embodiment, a multi-channel signal acquisition and calculation method is provided, which is applied to a multi-channel signal acquisition and calculation device. The device includes an acquisition card, a CPU, and a GPU. This method is executed by the GPU. Figure 2 It is a flowchart of the multi-channel signal acquisition and calculation method according to an embodiment of the present invention, as Figure 2 shown, and this process includes the following steps:

[0060] Step S201, receive the satellite baseband signal sent by the CPU.

[0061] Due to different hardware architectures, there are obvious differences in the data processing capabilities of the CPU and the GPU. The CPU has a more excellent ability to control the data stream and a relatively weak computing ability; while the GPU has more advantages in single-precision and double-precision floating-point operations and large-scale data operations. The concurrent threads adopted can process a large amount of parallel data at the same time. In order to improve the data processing efficiency, in this embodiment, the CPU+GPU broadband digital channelization algorithm parallel processing technology is adopted to collect and calculate the satellite baseband signal, so that the CPU and the GPU can take into account both efficiency and computing volume at the same time. When it comes to control flow and logical judgment, the CPU is used for processing, and when there is a large amount of data and many simple repetitive logical operations, the GPU is used to utilize the parallel processing ability of the GPU to improve the computing efficiency.

[0062] This satellite baseband signal is collected by the acquisition card and sent to the CPU. Specifically, the acquisition card includes multiple channels, can receive the satellite intermediate frequency signal in the satellite positioning system and convert it into a satellite baseband signal, and then send the satellite baseband signal to the CPU through the communication interface. The CPU then sends the received satellite baseband signal from the acquisition card to the GPU, and the GPU uses its own parallel processing ability to convert the satellite baseband signal into a satellite narrowband signal.

[0063] Step S202, divide the satellite baseband signal into each sub-channel.

[0064] When performing satellite positioning, there are multiple effective signal frequencies specified for the satellite intermediate frequency signal. The GPU can divide the satellite baseband signal into each sub-channel according to the multiple effective signal frequencies, so as to perform data processing on the satellite baseband signals with different effective signal frequencies respectively later. Among them, the number of sub-channels can be set according to requirements.

[0065] Step S203: Through each thread block in the GPU, based on the non-uniform digital channelization parameters corresponding to each sub-channel, perform non-uniform digital channelization processing on the satellite baseband signals in each sub-channel to obtain satellite narrowband signals corresponding to each sub-channel.

[0066] Digital channelization technology is a technology that divides broadband signals into multiple sub-channels through digital signal processing and realizes flexible switching and multiplexing. In this embodiment, the GPU performs non-uniform digital channelization processing on the satellite baseband signals in each sub-channel through its respective thread blocks. That is to say, the non-uniform digital channelization parameters corresponding to different sub-channels are different, and thus different satellite narrowband signals are obtained. The satellite narrowband signals will be sent by the GPU to the CPU to participate in the subsequent satellite positioning data calculation process to achieve satellite positioning. Since in this embodiment, the non-uniform digital channelization processing with large data volume and involving a large number of repetitive calculations is performed by the GPU instead of the CPU, and the thread blocks in the GPU work in parallel, the data processing efficiency is improved. Moreover, the signal acquisition and calculation processes of this application are all concentrated in the multi-channel signal acquisition and calculation device, eliminating the need for discrete acquisition, storage, and preprocessing devices and GPU parameter estimation devices, saving space.

[0067] The multi-channel signal acquisition and calculation method provided in this embodiment is applied to a multi-channel signal acquisition and calculation device, which includes an acquisition card, a CPU, and a GPU. This method is executed by the GPU. The method first receives the satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and sent to the CPU; then the satellite baseband signal is segmented into each sub-channel; finally, through each thread block in the GPU, based on the non-uniform digital channelization parameters corresponding to each sub-channel, perform non-uniform digital channelization processing on the satellite baseband signals in each sub-channel to obtain satellite narrowband signals corresponding to each sub-channel; the satellite narrowband signals are sent to the CPU for satellite positioning. In the above solution, by integrating the acquisition card, CPU, and GPU into the multi-channel signal acquisition and calculation device, the occupied space is saved and the signal transmission rate is improved; by combining the control flow ability of the CPU and the repetitive logical operation ability of the GPU, the satellite baseband signal is segmented into each sub-channel and the segmented satellite baseband signals are processed in parallel by each thread block in the GPU, enabling a large amount of data to be processed simultaneously, improving the signal processing efficiency and real-time performance.

[0068] In this embodiment, a multi-channel signal acquisition and calculation method is provided, which is applied to a multi-channel signal acquisition and calculation device. The device includes an acquisition card, a CPU, and a GPU. This method is executed by the GPU. Figure 3 It is a flowchart of the multi-channel signal acquisition and calculation method according to an embodiment of the present invention, as Figure 3 shown. The process includes the following steps:

[0069] Step S301: Receive the satellite baseband signal sent by the CPU.

[0070] The satellite baseband signal is collected by the acquisition card and sent to the CPU.

[0071] For details, please refer to Figure 2 Step S201 of the illustrated embodiment, which will not be elaborated here.

[0072] Step S302: Divide the satellite baseband signal into each sub-channel.

[0073] Specifically, the above step S302 includes:

[0074] Step S3021: Receive the bandwidth and center frequency of each sub-channel sent by the CPU.

[0075] When performing satellite positioning, multiple effective signal frequencies are specified for the satellite intermediate frequency signal, and the bandwidths and center frequencies corresponding to the multiple effective signal frequencies are stored in the CPU as the basis for the subsequent GPU to divide the satellite baseband signal into each sub-channel. When the GPU divides the satellite baseband signal, the CPU sends the bandwidth and center frequency of each sub-channel to the GPU, and the GPU receives the bandwidth and center frequency of each sub-channel sent by the CPU.

[0076] Step S3022: Divide the satellite baseband signal into each sub-channel according to the bandwidth and center frequency of each sub-channel, and obtain the satellite baseband signal corresponding to each sub-channel.

[0077] The center frequency is used to indicate the center frequency of the effective signal frequency, and the bandwidth is used to indicate the frequency range of the effective signal frequency. The GPU can divide the corresponding bandwidth and center frequency in the satellite baseband signal into the corresponding sub-channel according to the bandwidth and center frequency corresponding to each sub-channel, and obtain the satellite baseband signal corresponding to each sub-channel.

[0078] Step S303: Through each thread block in the GPU, perform non-uniform digital channelization processing on the satellite baseband signal in each sub-channel based on the non-uniform digital channelization parameters corresponding to each sub-channel, and obtain the satellite narrowband signal corresponding to each sub-channel.

[0079] The satellite narrowband signal is sent to the CPU for satellite positioning.

[0080] In an alternative embodiment, the non-uniform digital channelization parameters include a mixing phase factor, low-pass filter coefficients, and a decimation factor. Each sub-channel corresponds to different mixing phase factors, low-pass filter coefficients, and decimation factors, and the CPU is configured with the mixing phase factors, low-pass filter coefficients, and decimation factors corresponding to each sub-channel.

[0081] The GPU loads the mixing phase factors, low-pass filter coefficients, and decimation factors corresponding to each sub-channel from the CPU into its respective thread blocks, and each thread block performs digital down-conversion and decimation processing on the satellite baseband signals of each sub-channel based on the corresponding mixing phase factors, low-pass filter coefficients, and decimation factors to obtain the satellite narrowband signals corresponding to each sub-channel. The mixing phase factor is the phase change term introduced in the mixing process, which is used to indicate the phase offset of the signal after frequency conversion for the mixing process of digital down-conversion. The low-pass filter coefficients are used to indicate the filtering parameters of the low-pass filter, such as the cut-off frequency, in-band flatness, and rectangularity coefficient, etc., to filter and shape the signal. The decimation factor is used to indicate the decimation multiple to reduce the data volume of the signal. The satellite baseband signal is converted to the corresponding zero intermediate frequency through the mixing phase factors corresponding to each sub-channel, then filtered based on the low-pass filter coefficients corresponding to the sub-channel, and finally decimated according to the decimation factor corresponding to the sub-channel to obtain the satellite narrowband signal corresponding to the sub-channel.

[0082] Exemplarily, the CPU is configured with the FIR (finite impulse response) filter coefficients, decimation factors, and mixing phase factors corresponding to each sub-channel. The mixing phase factor is 2πf c / f s where f c is the center frequency of each channel, and f s is the sampling frequency of the input signal (the satellite baseband signal input to the sub-channel in this embodiment). Taking the GPU to calculate the satellite narrowband signal y k (n) corresponding to the k-th sub-channel as an example, the satellite baseband signal x(n) is first multiplied by the mixing factor corresponding to the k-th sub-channel to be converted to the zero intermediate frequency corresponding to the k-th sub-channel, and then convolved with the low-pass filter corresponding to the k-th sub-channel to filter based on the corresponding low-pass filter coefficients h k (n), and finally decimated according to the decimation factor D k corresponding to the k-th sub-channel to obtain the satellite narrowband signal y k (n).

[0083] In an alternative embodiment, the GPU generates corresponding data pointers based on the satellite narrowband signals corresponding to each sub-channel, and sends the data pointers to the CPU for the CPU to locate and read the satellite narrowband signals of each sub-channel for subsequent satellite positioning work.

[0084] Figure 4 It is a schematic flowchart of the non-uniform digital channelization process jointly performed by the CPU and GPU according to an embodiment of the present invention. As Figure 4 shown, first, the CPU applies for CPU memory and GPU video memory space. Then the CPU obtains input signal data (input satellite baseband signal), non-uniform filter bank, center frequencies of each sub-channel, input signal data length, low-pass filter coefficient length, etc., and sets the mixing phase factors, low-pass filter coefficients, and decimation factors corresponding to each sub-channel. The CPU copies and transfers these data from the memory to the GPU. The GPU loads these data into its own global memory and then distributes them to each thread block to run the kernel function in parallel for digital down-conversion, filter convolution, and decimation to obtain the satellite narrowband signals corresponding to each sub-channel, and generates data pointers corresponding to each satellite narrowband signal and sends them to the CPU. After receiving the output data of the non-uniform digital channelization process, the CPU releases the CPU memory and GPU video memory space to complete the non-uniform digital channelization process. Among them, since the decimation factors of each sub-channel are different, and thus the data lengths of the satellite narrowband signals output by each sub-channel are also different, it is necessary to first calculate the data lengths of the satellite narrowband signals of each sub-channel output and their starting positions in the memory according to the input data length and filter coefficient length to allocate cache space.

[0085] In an alternative embodiment, the GPU calls the time-frequency difference parameter estimation algorithm to calculate the time-frequency difference parameters based on the satellite narrowband signals corresponding to each sub-channel, and the time-frequency difference parameters can be used as the basis for subsequent calculation of satellite positioning data.

[0086] The multi-channel signal acquisition and calculation method provided in this embodiment is applied to a multi-channel signal acquisition and calculation device, which includes an acquisition card, a CPU, and a GPU. This method is executed by the GPU. First, the GPU receives the satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and sent to the CPU; then, the satellite baseband signal is segmented into each sub-channel; finally, through each thread block in the GPU, based on the non-uniform digital channelization parameters corresponding to each sub-channel respectively, the satellite baseband signal in each sub-channel is subjected to non-uniform digital channelization processing to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning. In the above solution, by integrating the acquisition card, CPU, and GPU into a multi-channel signal acquisition and calculation device, the occupied space is saved and the signal transmission rate is increased; by combining the control flow ability of the CPU and the repeated logical operation ability of the GPU, the satellite baseband signal is segmented into each sub-channel and the segmented satellite baseband signal is processed in parallel by each thread block in the GPU, enabling a large amount of data to be processed simultaneously, and improving the signal processing efficiency and real-time performance.

[0087] This embodiment provides a multi-channel signal acquisition and calculation device, as Figure 5 shown. The device includes an acquisition card, a CPU, and a GPU. The acquisition card is used to obtain the satellite baseband signal; the CPU is communicatively connected to the acquisition card and is used to receive the satellite baseband signal sent by the acquisition card; the GPU is communicatively connected to the CPU and is used to receive the satellite baseband signal sent by the CPU, and segment the satellite baseband signal into each sub-channel, and through each thread block in the GPU, based on the non-uniform digital channelization parameters corresponding to each sub-channel respectively, perform non-uniform digital channelization processing on the satellite baseband signal in each sub-channel to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning.

[0088] Figure 5 The working principle of the multi-channel signal acquisition and calculation device shown is as follows:

[0089] Figure 6It is a schematic diagram for comparing the structures of a CPU and a GPU according to an embodiment of the present invention. The serial processing of a single CPU often has difficulty in meeting the real-time processing and analysis of large-scale data. While a GPU can batch process large-scale data with repetitive operations and has the same data processing method for the data stored in each internal arithmetic unit. Therefore, the GPU has a lower requirement for the complexity of the running program. This highly parallel structure significantly shortens the data processing time of the GPU. Thus, the GPU has more advantages than the CPU in terms of large amounts of data and repetitive operations. The controller and registers occupy most of the area in the CPU. In the GPU, however, there are more ALUs (Arithmetic Logic Units). Due to the differences in the internal chip structures, the GPU is more suitable for processing large-scale data rather than data caching and flow control. To improve the data processing efficiency, in this embodiment, a CPU+GPU broadband digital channelization algorithm parallel processing technology is adopted to collect and calculate satellite baseband signals, enabling the CPU and GPU to take both efficiency and computational volume into account simultaneously. When it comes to control flow and logical judgment, the CPU is used for processing. When there is a large amount of data and many simple repetitive logical operations, the GPU is used to utilize the parallel processing ability of the GPU to improve the computational efficiency. It should be noted that Figure 6 in which, Dram (Dynamic Random Access Memory) is a dynamic random access memory.

[0090] The GPU contains multiple thread blocks (block). The GPU needs to determine the number of required thread blocks. In an optional implementation, these thread blocks form a two-dimensional grid (grid). The number of thread blocks included in the Y dimension of the two-dimensional grid is determined based on the number of sub-channels and is used to indicate the signal frequency. The number of thread blocks included in the X dimension of the two-dimensional grid is determined based on the maximum data length of the satellite baseband signals in each sub-channel and is used to indicate the signal length, that is, the signal time. Among them, each thread block includes multiple threads (thread). Each thread block distributes the allocated satellite baseband signals to its multiple threads, and the multiple threads process the allocated satellite baseband signals in parallel, thereby obtaining the satellite narrowband signals corresponding to the thread block. Exemplarily, each thread block includes 512 threads. The number of thread blocks included in the X dimension of the two-dimensional grid is ceil(MaxOneChBaseSigLength / 512), where MaxOneChBaseSigLength is the maximum data length of the satellite baseband signals in each sub-channel. Taking the maximum data length of the satellite baseband signals in each sub-channel as 10,000 as an example, if each thread block has 512 threads, then the number of required thread blocks is 10,000 / 512 = 19.5, and rounding up gives 20. A total of 20 thread blocks are required. Exemplarily, Figure 7Schematic diagram of a GPU performing digital downconversion and decimation through each thread block according to an embodiment of the present invention. The GPU includes thread blocks Block1 to BlockN, and Block1 includes threads 1 to N. Digital downconversion and decimation operations are performed in parallel among the thread blocks, and digital downconversion and decimation operations are performed in parallel among the threads in each thread block.

[0091] In an alternative embodiment, the acquisition card includes ADC units and FPGAs of multiple channels, with each channel corresponding to one FPGA. The ADC units of the multiple channels are used to acquire satellite intermediate-frequency analog signals and perform analog-to-digital conversion to obtain satellite intermediate-frequency signals; the FPGAs are communicatively connected to the corresponding ADC units and are used to perform digital downconversion processing on the satellite intermediate-frequency signals to obtain satellite baseband signals. The specific number of channels is set according to requirements. For example, it is set to 4 channels, and the satellite baseband signals corresponding to each channel are respectively subjected to sub-channel segmentation and non-uniform digital channelization processing.

[0092] Figure 8 Schematic flowchart of an FPGA performing digital downconversion processing according to an embodiment of the present invention. As Figure 8 shown, the ADC unit inputs AD data (satellite intermediate-frequency signal) into the FPGA. The FPGA first multiplies the quadrature local oscillator signal (including a sine oscillation signal corresponding to the Q channel and a cosine oscillation signal corresponding to the I channel) generated by the direct digital frequency synthesizer DDS with the satellite intermediate-frequency signal for mixing to obtain an initial satellite baseband signal for the I channel and an initial satellite baseband signal for the Q channel, and then sequentially processes the initial satellite baseband signal for the I channel through the cascaded integrator-comb filter CIC, compensation FIR filter CFIR, and post FIR filter PFIR for the I channel, and sequentially processes the initial satellite baseband signal for the Q channel through the cascaded integrator-comb filter CIC, compensation FIR filter CFIR, and post FIR filter PFIR for the Q channel to obtain the satellite baseband signal for the I channel and the satellite baseband signal for the Q channel.

[0093] Figure 9 Schematic flowchart of implementing digital channelization by an ADC, an FPGA, and a GPU according to an embodiment of the present invention. The ADC unit transmits the satellite intermediate-frequency signal to the FPGA. The FPGA converts the satellite intermediate-frequency signal into a satellite baseband signal and then transmits it to the GPU. The GPU divides the satellite baseband signal into 256 sub-channels through a channelization algorithm. Taking a satellite intermediate-frequency signal of 140 MHz ± 40 MHz, a satellite baseband signal of 80 MHz, and division into 256 sub-channels as an example.

[0094] In an alternative embodiment, the acquisition card is further configured to obtain an external clock signal and a second pulse signal; the external clock signal is used to be coherent with the satellite positioning system in frequency; the second pulse signal is used to indicate the acquisition card to perform data acquisition at the rising edge.

[0095] In an alternative embodiment, a monitoring and management software is also provided in the multi-channel signal acquisition and calculation device, which is used for device management and resource monitoring, and can provide visualization services for the multi-channel signal acquisition and calculation process. Exemplarily, the monitoring and management software interface includes the serial numbers of each channel and each sub-channel, the center frequency, bandwidth, amplitude, sampling rate, sampling depth, carrier-to-noise ratio, etc. of the acquired input signal, and also includes the time of signal acquisition, the size of the acquisition file, the disk rate, etc. Users can set the acquisition channels, acquisition methods, acquisition quantities, clock frequencies, filter coefficients, channelization numbers, etc. through this interface.

[0096] In an alternative embodiment, the multi-channel signal acquisition and calculation device further includes a solid-state system disk, a RAID card, and a disk array. The solid-state system disk is used to install the operating system. The RAID card and the disk array form a RAID5 disk array, which is used as a high-speed data storage disk to store data during the multi-channel signal acquisition and calculation process. The remote control and data interaction are that the multi-channel signal acquisition and calculation device receives the parameters and instructions sent by the system control software in the satellite positioning system.

[0097] This embodiment provides a satellite positioning system, including a satellite timekeeping device, a positioning processing device, and a multi-channel signal acquisition and calculation device as described in Figure 5 the embodiment or any corresponding embodiment thereof.

[0098] The multi-channel signal acquisition and calculation device serves as an edge computing device in the satellite positioning system. Edge computing is a computing mode that moves computing tasks and data storage to the edge of the network, that is, close to the data source or the user terminal. This computing mode aims to reduce data transmission latency, improve processing speed, and reduce the processing burden on the data center. Edge computing processes by moving the operations of applications, data, and services from the central node of the network to the edge nodes logically on the network, thereby accelerating the processing and transmission speed of data and reducing latency.

[0099] The satellite timekeeping device is used to send an external clock signal to the multi-channel signal acquisition and calculation device for the multi-channel signal acquisition and calculation device to be coherent with the satellite positioning system in frequency.

[0100] The positioning processing device is communicatively connected to the multi-channel signal acquisition and calculation device, and is configured to receive the output result of the multi-channel signal acquisition and calculation device, and calculate a satellite positioning result based on the output result. The output result of the multi-channel signal acquisition and calculation device may be satellite narrowband signals corresponding to each sub-channel obtained by processing a satellite baseband signal, or time-frequency difference parameters obtained by further calculating the satellite narrowband signals corresponding to each sub-channel. The satellite positioning result may be geographical location information, time, speed data, altitude, etc.

[0101] As one or more specific application embodiments of the embodiments of the present invention, the optimal implementation scheme or the scheme that the inventor most wants to embody will be described below in combination with specific application scenarios.

[0102] Figure 10 It is a connection relationship diagram of a multi-channel signal acquisition and calculation device according to an embodiment of the present invention. The multi-channel signal acquisition and calculation device simultaneously has the capabilities of the acquisition, storage, and preprocessing device and the GPU parameter estimation device in the related art, integrates a data acquisition card, a storage array, and 4 GPU cards in one device, reduces the transmission delay of the satellite baseband signal, and reduces the rack installation space of the discrete devices. The multi-channel signal acquisition and calculation device greatly improves the processing capabilities of the GPU and the CPU, adopts a flexible heterogeneous signal processing method of FPGA + CPU + GPU, enhances the processing capability of the input signal within an 80MHz bandwidth, processes the input signal within the effective bandwidth through digital down-conversion in the FPGA, and realizes multi-channel channelization in the GPU to perform refined analysis on the input signal. The key technology of GPU broadband digital channelization specifically processes the effective part of the input signal, so that only the processing results of the effective narrowband part need to be stored, improving the storage efficiency of the disk array.

[0103] The multi-channel signal acquisition and calculation device can meet the requirements of multi-class signal channelized acquisition and pre-computation processing. As the edge computing core node of the satellite positioning system, the multi-channel signal acquisition device has the capabilities of real-time signal acquisition and processing and high-performance computing. Among them, in terms of real-time signal acquisition and processing, it supports the acquisition and digital channelization processing of 4-way satellite intermediate frequency signals, meeting requirements such as unified time-frequency standards and multi-channel signal channelization processing. In terms of computing, it supports users to deploy local computing programs for data processing and supports dynamic allocation of computing resources. At the same time, the multi-channel signal acquisition device has remote status monitoring and remote control functions. The multi-channel signal acquisition and calculation device mainly completes signal preprocessing functions such as high-speed acquisition, real-time storage to disk, and digital down-conversion of satellite intermediate frequency signals corresponding to four channels, and supports the function of calling the GPU algorithm dynamic library for signal processing and analysis of the disk data.

[0104] The multi-channel signal acquisition and calculation device mainly consists of a 4U rack-mounted high-performance server (U represents the rack height unit rack unit), a data acquisition card, a GPU calculation card, a GPU channelization algorithm, and monitoring and management software.

[0105] The 4U rack-mounted high-performance server is equipped with a data acquisition card, an SSD disk array, a GPU, etc., which are mainly used for high-performance computing (GPU) and high-speed data storage disks (SSD disk arrays). At the same time, system software runs on this server. Exemplarily, the model of this server is HWA-ZCR-4U-2401.

[0106] The data acquisition card is installed inside the 4U rack-mounted high-performance server and is used to receive satellite intermediate frequency signals, clock signals, and externally input second pulse signals, etc. The digital quantization processing of satellite intermediate frequency analog signals is realized through the ADC unit in the data acquisition card, and the analog-to-digital conversion is performed to send the satellite intermediate frequency signal to the FPGA in the module for digital down-conversion processing (decimation factor 2 to 16384). The processed data is sent to the 4U rack-mounted high-performance server through the PCIE interface for subsequent processing. The data acquisition card is the core component of the multi-channel signal acquisition and calculation device, mainly used for continuously acquiring wideband and narrowband signals and preprocessing the acquired signals. The sampling frequency of the data acquisition card supports 30MHz to 250MHz, and it can acquire target signals of conventional communication signals 70MHz ± 18MHz and 140MHz ± 40MHz. It supports narrowband acquisition service, broadband acquisition service, continuous acquisition service based on the data acquisition card, supports output to files and memory, supports ADC direct sampling mode and DDC digital down-conversion preprocessing mode, supports clock modes such as internal clock, external clock, and external reference, supports two trigger modes of internal trigger and external trigger, and supports working modes such as immediate stop after acquisition, fixed-length acquisition, timed acquisition, segmented acquisition, and automated acquisition of preset tasks. The advantage of the data acquisition card is that it has high-precision inter-channel consistency synchronization indicators for ADC. The intra-board synchronization and inter-board synchronization performance of the data acquisition card are the premise and basis for the estimation of time-frequency difference parameters of non-cooperative radiation sources (such as radio frequency signals emitted by satellites). The intra-board synchronization indicator is 60ps, and the inter-board synchronization indicator is 1ns, while the accuracy of time-frequency difference parameter estimation is at the microsecond level. The superior intra-board synchronization indicator and inter-board synchronization indicator of the data acquisition card effectively ensure the accuracy of radiation source time-frequency difference parameter estimation. Exemplarily, the model of this data acquisition card is HWA-PCIE-5901.

[0107] For the GPU computing card and the GPU channelization algorithm, 4 GPUs are configured in the multi-channel signal acquisition and computing device to achieve high-performance computing. It supports the multi-channel unequal-interval GPU digital channelization algorithm, can process DDC (Digital Down-Conversion) baseband data in real time / offline, perform channelization processing in parallel, reduce the data sampling frequency, improve the real-time performance of processing, and effectively extract target data. Exemplarily, a heterogeneous mode of CPU and GPU is selected to achieve high-performance computing, and the GPU channelization algorithm can be completed with higher efficiency and accuracy. The programming architecture of CPU+GPU has better flexibility, reliability and efficiency than using only CPU or GPU alone, greatly improving the processing power of the GPU. The acquisition and storage preprocessing device in the related technology is equipped with 1 GPU computing card, and the GPU parameter estimation device is equipped with 2 GPU computing cards. A total of 3 GPU computing cards are used in the two types of devices. However, the multi-channel signal acquisition and computing device in this embodiment is configured with 4 NVIDIA high-performance GPU computing cards and has the ability to be extended to 6 GPU computing cards, comprehensively exceeding traditional devices in terms of indicators such as the number of GPU computing cards, the number of threads and the number of cores.

[0108] The monitoring and management software is deployed on a 4U rack-mounted high-performance acquisition server, mainly realizing functions such as signal acquisition, GPU resource scheduling and management, device management, real-time monitoring, statistics and scheduling of resource usage. The software supports the system software call of users, and the software coding and interface specifications meet the requirements of the user system software. It has remote control and local control functions. In the remote control mode, it communicates with third-party programs through the API interface or the network communication interface and synchronously refreshes the local resource status.

[0109] Figure 11 It is a motherboard slot sorting diagram of the multi-channel signal acquisition and computing device according to the embodiment of the present invention. As Figure 11 shown, slots 1 to 10 on the motherboard are both two standard PCIE slot widths, and the thickness of the GPU card is both two standard PCIE widths. In the design, slots 1, 2, 7 and 8 are used to install GPU cards to meet the installation dimension requirements. Slots 3, 9 and 10 can be used as expansion slots for three GPU computing cards.

[0110] In terms of heat dissipation, considering that the heat dissipation of the acquisition card is relatively large and the heat dissipation of the RAID control card and the 10 Gigabit network card is relatively small, the acquisition card, the 10 Gigabit network card, the RAID card and the RAID card capacitor are inserted into slots 4, 5 and 6 respectively, which can balance the heat distribution inside the chassis. The heat dissipation capacity configured by the system fully meets the heat dissipation requirements of 6 GPU cards.

[0111] In this embodiment, a multi-channel signal acquisition and calculation device is further provided. This device is used to implement the above-mentioned embodiment and the preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0112] This embodiment provides a multi-channel signal acquisition and calculation device. This device is applied to a multi-channel signal acquisition and calculation device, which includes an acquisition card, a CPU, and a GPU. This device is set in the GPU. As Figure 12 shown, this device includes:

[0113] A receiving module 1201, which is used to receive the satellite baseband signal sent by the CPU; this satellite baseband signal is acquired by the acquisition card and sent to the CPU.

[0114] A splitting module 1202, which is used to split the satellite baseband signal into each sub-channel.

[0115] A processing module 1203, which is used to perform non-uniform digital channelization processing on the satellite baseband signal in each sub-channel through each thread block in the GPU, based on the non-uniform digital channelization parameters respectively corresponding to each sub-channel, to obtain the satellite narrowband signal corresponding to each sub-channel; this satellite narrowband signal is sent to the CPU for satellite positioning.

[0116] In an optional implementation manner, this receiving module is further used to receive the bandwidth and center frequency point of each sub-channel sent by the CPU.

[0117] This splitting module is further used to split the satellite baseband signal into each sub-channel according to the bandwidth and center frequency point of each sub-channel, to obtain the satellite baseband signal corresponding to each sub-channel.

[0118] In an optional implementation manner, the non-uniform digital channelization parameters include a mixing phase factor, a low-pass filter coefficient, and a decimation factor; wherein, each sub-channel corresponds to different mixing phase factors, low-pass filter coefficients, and decimation factors.

[0119] This processing module is further used to:

[0120] Load the mixing phase factor, low-pass filter coefficient, and decimation factor corresponding to each sub-channel into the corresponding thread block, and perform digital down-conversion and decimation processing on the satellite baseband signal in each sub-channel through each thread block based on the corresponding mixing phase factor, low-pass filter coefficient, and decimation factor, to obtain the satellite narrowband signal corresponding to each sub-channel.

[0121] The further function descriptions of the above-mentioned modules and units are the same as those in the corresponding embodiments above, and will not be elaborated here.

[0122] The multi-channel signal acquisition and calculation device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0123] The embodiment of the present invention also provides a computer device having the above-mentioned Figure 12 multi-channel signal acquisition and calculation device shown.

[0124] Please refer to Figure 13 , Figure 13 which is a schematic structural diagram of a computer device provided by an alternative embodiment of the present invention. As shown in Figure 13 , the computer device includes: one or more processors 10, a memory 20, and an interface for connecting each component, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (such as a server array, a set of blade servers, or a multi-processor system). Figure 13 In

[0125] FIG. 19, one processor 10 is taken as an example.

[0126] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0127] The memory 20 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device and the like. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 may optionally include a memory remotely provided with respect to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0128] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 20 may further include a combination of the above types of memories.

[0129] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 may be connected through a bus or other means, Figure 13 Taking connection through a bus as an example.

[0130] The input device 30 can receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (such as an LED), and a tactile feedback device (such as a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some alternative embodiments, the display device may be a touch screen.

[0131] Embodiments of the present invention also provide a computer-readable storage medium. The method according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored as such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.

[0132] A part of the present invention can be applied as a computer program product, such as computer program instructions. When executed by a computer, through the operation of the computer, the method and / or technical solution according to the present invention can be invoked or provided. Those skilled in the art should understand that the forms of existence of computer program instructions in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Herein, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible by the computer.

[0133] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the protection scope of the present invention.

Claims

1. A multi-channel signal acquisition and calculation method, characterized in that The method is applied to a multi-channel signal acquisition and calculation device, which includes an acquisition card, a CPU, and a GPU. The method is executed by the GPU and includes: Receiving the satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and sent to the CPU; Dividing the satellite baseband signal into each sub-channel; Through each thread block in the GPU, based on the non-uniform digital channelization parameters corresponding to each sub-channel respectively, performing non-uniform digital channelization processing on the satellite baseband signal in each sub-channel to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning.

2. The method according to claim 1, characterized in that, The method further includes: Receiving the bandwidth and center frequency of each sub-channel sent by the CPU; According to the bandwidth and center frequency of each sub-channel, dividing the satellite baseband signal into each sub-channel to obtain the satellite baseband signal corresponding to each sub-channel.

3. The method according to claim 1 or 2, characterized in that, The non-uniform digital channelization parameters include a mixing phase factor, a low-pass filter coefficient, and a decimation factor; wherein, each sub-channel corresponds to different mixing phase factors, low-pass filter coefficients, and decimation factors; The method further includes: Loading the mixing phase factor, low-pass filter coefficient, and decimation factor corresponding to each sub-channel into the corresponding thread block, and through each thread block, performing digital down-conversion and decimation processing on the satellite baseband signal of each sub-channel based on the corresponding mixing phase factor, low-pass filter coefficient, and decimation factor to obtain the satellite narrowband signal corresponding to each sub-channel.

4. A multi-channel signal acquisition and calculation device, characterized in that The device is applied to a multi-channel signal acquisition and calculation device, which includes an acquisition card, a CPU, and a GPU. The device is set in the GPU and includes: A receiving module, configured to receive the satellite baseband signal sent by the CPU; the satellite baseband signal is acquired by the acquisition card and sent to the CPU; A dividing module, configured to divide the satellite baseband signal into each sub-channel; A processing module, configured to perform non-uniform digital channelization processing on the satellite baseband signal in each sub-channel through each thread block in the GPU based on the non-uniform digital channelization parameters corresponding to each sub-channel respectively to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning.

5. A multi-channel signal acquisition and calculation device, characterized in that, Including: An acquisition card, configured to acquire the satellite baseband signal; A CPU, communicatively connected to the acquisition card, configured to receive the satellite baseband signal sent by the acquisition card; A GPU, communicatively connected to the CPU, configured to receive the satellite baseband signal sent by the CPU, divide the satellite baseband signal into each sub-channel, and through each thread block in the GPU, perform non-uniform digital channelization processing on the satellite baseband signal in each sub-channel based on the non-uniform digital channelization parameters corresponding to each sub-channel respectively to obtain the satellite narrowband signal corresponding to each sub-channel; the satellite narrowband signal is sent to the CPU for satellite positioning.

6. The device according to claim 5, characterized in that, Each of the thread blocks forms a two-dimensional grid; the number of thread blocks included in the Y dimension of the two-dimensional grid is determined based on the number of sub-channels; the number of thread blocks included in the X dimension of the two-dimensional grid is determined based on the maximum data length of the satellite baseband signal in each sub-channel.

7. The device according to claim 5 or 6, characterized in that, The acquisition card includes: An ADC unit with multiple channels, which is used to collect the satellite intermediate-frequency analog signal and perform analog-to-digital conversion to obtain the satellite intermediate-frequency signal; An FPGA, which is communicatively connected to the ADC unit and is used to perform digital down-conversion processing on the satellite intermediate-frequency signal to obtain the satellite baseband signal.

8. A computer device, characterized in that, It includes: A memory and a processor, which are communicatively connected to each other. Computer instructions are stored in the memory, and the processor executes the computer instructions to execute the multi-channel signal acquisition and calculation method according to any one of claims 1 to 3.

9. A computer-readable storage medium, characterized in that, Computer instructions are stored on the computer-readable storage medium, and the computer instructions are used to cause the computer to execute the multi-channel signal acquisition and calculation method according to any one of claims 1 to 3.

10. A computer program product, characterized in that, It includes computer instructions, and the computer instructions are used to cause the computer to execute the multi-channel signal acquisition and calculation method according to any one of claims 1 to 3.

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