Satellite receiver signal processing method and device

Abstract

The embodiment of the invention provides a satellite receiver signal processing method and device, and the method comprises the steps: carrying out the demodulation processing of a received signal, and obtaining a baseband signal; performing correlation calculation processing on the baseband signal and a local correlation sequence to obtain a correlation value; constructing a signal space based on the correlation value; performing linear filtering processing on the correlation value of the signal space to obtain a linearly filtered signal space; based on the signal space after linear filtering, the maximum correlation value under the same Doppler frequency and different code phase delays in the first dimension is searched, the sum of the distances between the maximum correlation value and the correlation values under the same Doppler frequency and other code phase delays is calculated, and the maximum distance is selected from the sum of the distances corresponding to the Doppler frequencies; performing nonlinear filtering processing on the correlation value of the Doppler frequency corresponding to the maximum distance to obtain a correlation value after nonlinear filtering; and determining whether a target signal exists based on the correlation value after nonlinear filtering. The performance of capturing the target signal can be improved.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, and in particular to a satellite receiver signal processing method and apparatus. Background Technology

[0002] The satellite signal strength received by the satellite receiver front end is much lower than the noise floor, making it highly susceptible to noise and interference. Suppressing interference and successfully acquiring and tracking weak satellite signals are key issues in satellite receiver design. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a satellite receiver signal processing method and apparatus.

[0004] To achieve the above objectives, this application provides a satellite receiver signal processing method, comprising: The received signal is demodulated to obtain the baseband signal; The baseband signal is correlated with the local correlation sequence to obtain correlation values ​​for different Doppler frequencies and different code phase delays. Based on the correlation values, a signal space is constructed; wherein, the signal space includes multiple cells formed with Doppler frequency as the first dimension and code phase delay as the second dimension, and the value of each cell is the correlation value corresponding to the Doppler frequency in the first dimension and the code phase delay in the second dimension; The correlation values ​​of the signal space are linearly filtered to obtain the linearly filtered signal space. Based on the linearly filtered signal space, find the maximum correlation value under the same Doppler frequency and different code phase delays in the first dimension, calculate the sum of the distances between the maximum correlation value and each correlation value under the same Doppler frequency and other code phase delays, and select the maximum distance from the sum of the distances corresponding to each Doppler frequency. The correlation value of the Doppler frequency corresponding to the maximum distance is subjected to nonlinear filtering to obtain the nonlinearly filtered correlation value; Based on the correlation value after nonlinear filtering, it is determined whether a target signal exists.

[0005] Optionally, the correlation values ​​in the signal space are subjected to linear filtering to obtain linearly filtered correlation values, including: For each cell in the signal space, determine the neighboring cells of that cell; By using a preset linear mask to perform a weighted summation with the cell and its neighboring cells, the correlation value of the cell after linear filtering is obtained.

[0006] Optionally, determining the neighboring units of each unit in the signal space includes: For each element at the same Doppler frequency in the first dimension, taking the current element as the central element, proceed forward and backward along the second dimension. n Each unit is considered a neighborhood unit; The correlation value of the current cell after linear filtering is obtained by weighted summation of the current cell and its neighboring cells using a preset linear mask. The method is as follows: ; in, The correlation value is the result of linear filtering. For the first i The linear masking coefficients of each linear masking unit, and the linear masking coefficient of the central linear masking unit. The value can be 1 or 1.2. For code phase accuracy, For code phase delay, f D The frequency is the Doppler frequency.

[0007] Optionally, the correlation value of the Doppler frequency corresponding to the maximum distance is subjected to nonlinear filtering to obtain the nonlinearly filtered correlation value, including: The correlation values ​​of each unit of the Doppler frequency corresponding to the maximum distance are filtered using a preset nonlinear mask to obtain the nonlinear filtered correlation value; wherein, the nonlinear mask is determined according to the distribution characteristics of the interference signal and the satellite signal.

[0008] Optionally, the nonlinear mask includes multiple nonlinear mask units; the correlation value of the Doppler frequency corresponding to the maximum distance is nonlinearly filtered to obtain the nonlinearly filtered correlation value, the method being: ; in, f Dd The Doppler frequency corresponding to the maximum distance. The correlation value is the result of nonlinear filtering. The nonlinear mask coefficients of the central nonlinear mask element. For the first i The nonlinear mask coefficients of each nonlinear mask element are calculated as follows: ; in, S med This represents the median of the correlation values ​​of the cells covered by the nonlinear mask.

[0009] This application also provides a satellite receiver signal processing apparatus, including: The demodulation module is used to demodulate the received signal to obtain the baseband signal; The correlation calculation module is used to perform correlation calculation processing on the baseband signal and the local correlation sequence to obtain correlation values ​​with different Doppler frequencies and different code phase delays; A construction module is used to construct a signal space based on the correlation value; wherein the signal space includes multiple cells formed with Doppler frequency as the first dimension and code phase delay as the second dimension, and the value of each cell is the correlation value corresponding to the Doppler frequency in the first dimension and the code phase delay in the second dimension; A linear filtering module is used to perform linear filtering on the correlation values ​​of the signal space to obtain a linearly filtered signal space. The search module is used to search for the maximum correlation value under different code phase delays at the same Doppler frequency in the first dimension based on the linearly filtered signal space, calculate the sum of the distances between the maximum correlation value and each correlation value under other code phase delays at the same Doppler frequency, and select the maximum distance from the sum of the distances corresponding to each Doppler frequency. The nonlinear filtering module is used to perform nonlinear filtering on the correlation value of the Doppler frequency corresponding to the maximum distance to obtain the nonlinearly filtered correlation value. The capture module is used to determine whether a target signal exists based on the correlation value after nonlinear filtering.

[0010] Optionally, the linear filtering module is used to determine the neighboring units of each unit in the signal space; and to perform a weighted summation of the unit and its neighboring units using a preset linear mask to obtain the correlation value of the unit after linear filtering.

[0011] Optionally, the linear filtering module is used to, for each unit at the same Doppler frequency in the first dimension, take the current unit as the center unit and filter forward and backward along the second dimension. n Each unit is considered a neighborhood unit; The correlation value of the current cell after linear filtering is obtained by weighted summation of the current cell and its neighboring cells using a preset linear mask. The method is as follows: ; in, The correlation value is the result of linear filtering. For the first i The linear masking coefficients of each linear masking unit, and the linear masking coefficient of the central linear masking unit. The value can be 1 or 1.2. For code phase accuracy, For code phase delay, f D The frequency is the Doppler frequency.

[0012] Optionally, the nonlinear filtering module is used to filter the correlation values ​​of each unit of the Doppler frequency corresponding to the maximum distance using a preset nonlinear mask to obtain the nonlinear filtered correlation value; wherein, the nonlinear mask is determined according to the distribution characteristics of the interference signal and the satellite signal.

[0013] Optionally, the nonlinear mask includes multiple nonlinear mask units; The correlation value of the Doppler frequency corresponding to the maximum distance is subjected to nonlinear filtering to obtain the nonlinearly filtered correlation value. The method is as follows: ; Where n' is the radius of the nonlinear mask; f Dd The Doppler frequency corresponding to the maximum distance. The correlation value is the result of nonlinear filtering. The nonlinear mask coefficients of the central nonlinear mask element. For the first i The nonlinear mask coefficients of each nonlinear mask element are calculated as follows: ; in, S med This represents the median of the correlation values ​​of the cells covered by the nonlinear mask.

[0014] As can be seen from the above description, the satellite receiver signal processing method and apparatus provided in this application demodulate the received signal to obtain a baseband signal, perform correlation calculation on the baseband signal and a local correlation sequence to obtain a correlation value, construct a signal space based on the correlation value, perform linear filtering on the correlation value of the signal space to obtain a linearly filtered signal space, find the maximum correlation value under different code phase delays at the same Doppler frequency in the first dimension based on the linearly filtered signal space, calculate the sum of distances between the maximum correlation value and each correlation value under other code phase delays at the same Doppler frequency, select the maximum distance from the sum of distances corresponding to each Doppler frequency, perform nonlinear filtering on the correlation value of the Doppler frequency corresponding to the maximum distance to obtain a nonlinearly filtered correlation value, and determine whether a target signal exists based on the nonlinearly filtered correlation value. This application can effectively suppress interference and improve positioning accuracy. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the method flow of an embodiment of this application; Figure 2 This is a schematic diagram of a method flow according to another embodiment of this application; Figure 3 This is a schematic diagram of the linear decomposition signal in some embodiments; Figure 4 This is a schematic diagram of the linear filtering process in an embodiment of this application; Figure 5 This is a schematic diagram illustrating the linear filtering principle of an embodiment of this application; Figure 6 This is a block diagram of the device structure according to an embodiment of this application; Figure 7 This is a block diagram of the electronic device structure according to an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] In related technologies, satellite receivers receive signals including useful satellite signals, noise, and interference. Satellite signals are extremely weak, often submerged in noise and interference, and exhibit significant Doppler shift. The receiver demodulates the received signal to obtain a baseband signal, which is then correlated with a local correlation sequence. Successful acquisition of the target signal occurs when the code phases of the baseband signal and the local correlation sequence are aligned and their carrier frequencies are consistent. However, the presence of interference distorts the statistical characteristics of the correlation results. Interference generates a series of peak values ​​in the Doppler frequency dimension through the correlation process. These false peaks may completely overwhelm or mask the peak values ​​of the satellite signal, rendering the acquisition method that seeks the maximum value ineffective and preventing accurate acquisition of the target signal.

[0020] In view of this, the present application provides a satellite receiver signal processing method, which filters the correlation value of the baseband signal and the local correlation sequence correlation operation to suppress spurious correlation peaks caused by interference and enhance the satellite signal peak. In the interference environment, it can reliably and effectively capture weak satellite signals without relying on any prior knowledge of interference, thereby improving positioning accuracy. Moreover, the computational complexity is not high, which can meet the computational complexity requirements of real-time receivers.

[0021] The technical solution of this application will be further described in detail below through specific embodiments.

[0022] like Figure 1 , 2 As shown in the figure, this application provides a satellite receiver signal processing method, characterized in that it includes: S101: Demodulate the received signal to obtain the baseband signal; In this embodiment, the received signal from the receiver is amplified and filtered, down-converted to a lower intermediate frequency (IF) signal, converted into a digital signal, multiplied with the local carrier signal, and then low-pass filtered to obtain the baseband signal. This baseband signal includes in-phase and quadrature components, and can completely represent the amplitude and phase of the signal. The specific demodulation process and method are conventional methods in the art, and this embodiment does not provide a detailed description of the specific principles, processes, and methods of demodulation.

[0023] S102: Perform correlation calculations on the baseband signal and the local correlation sequence to obtain correlation values ​​for different Doppler frequencies and different code phase delays; In this embodiment, to capture satellite signals, the receiver locally constructs a local correlation sequence corresponding to the satellite signals. This sequence is used to perform correlation operations with the baseband signals, and the calculated correlation value is used to determine whether a target signal exists. This embodiment does not provide a detailed description of the specific method for constructing the local correlation sequence.

[0024] Specifically, the baseband signal under a specific Doppler frequency shift and a specific code phase delay is correlated with the corresponding local correlation sequence under the same Doppler frequency shift and code phase delay. The correlation value between the baseband signal and the local correlation sequence under the specific Doppler frequency shift and code phase delay is obtained, expressed as: (1) in, To achieve Doppler frequency shift f D Code phase delay The correlation function between the baseband signal and the local correlation sequence can be calculated using a mutual ambiguity function at the Doppler frequency shift. f D Code phase delay The degree of relevance, The modulus of the correlation function, i.e., the correlation value. For the in-phase component of the correlation function, These are the orthogonal components of the correlation function.

[0025] In some methods, the correlator of the receiver can be used to perform correlation calculations between the baseband signal and the local correlation sequence. Since correlation and coherence integration are linear operations, the correlation function performed by the correlator is... It can be viewed as a linear superposition of contributions from three independent signal sources: satellite signal, noise, and interference. Thus, the complex correlation output can be decomposed into three parts corresponding to the three independent signal sources, and modeled and analyzed separately.

[0026] like Figure 3 As shown, S IF The useful satellite signal portion of the received signal. N IF The noise component in the received signal. I IF To detect interference signals in the received signal, linear calculations (correlation function calculations) are performed on the baseband signals of the three signal components and the local correlation sequence. Then, the modulus of the correlation function is taken. Based on the principle of linear superposition, the signal output by the correlator can be linearly decomposed to obtain the contribution of the satellite signal. S r Contribution of noise signal N i Contribution to interference signals I n The signal is decomposed into three parts. In this way, by linearly decomposing the signal, the characteristics of the interference signal can be studied independently, and the specific peak patterns generated by the interference can be analyzed without considering the coupling effect between noise and the useful signal. Thus, filters can be designed for the interference signal, and the interference signal in the received signal can be filtered out to improve the accuracy of capturing the useful signal.

[0027] In some methods, the period for the C / A code (coarse acquisition code) transmitted by the satellite is 1ms, and the spectral interval is 1kHz. When continuous wave interference at a fixed frequency exists, the spectral line of the interference signal coincides with a certain spectral line of the C / A code, enhancing the signal power. Within a certain integration time, the continuous wave interference will act on different C / A code spectral lines within the Doppler frequency offset range of the satellite signal. Therefore, after calculating the correlation value, it can be analyzed that the continuous wave interference component presents a series of peaks in the Doppler frequency dimension. This type of continuous wave interference signal affects the correlation output. The contribution can be expressed as: (2) (3) (4) in, f r The C / A code spectral line spacing is 1 kHz. T i For the coherent integration time, A int The amplitude of the interference signal, C k Let be the nth spectral line coefficient, representing the coupling strength between the frequency of the interfering signal and the spectral line of the nearest C / A code. f IF For the frequency of the baseband signal, f int The frequency of the interference signal.

[0028] As the coherent integration time increases, the contributions of satellite signals and interference signals to the correlation output increase, thus suppressing the noise signal power on an average basis. In equation (2) sinc The width of each sidelobe of the function is inversely proportional to the integration period; that is, the longer the integration period, the narrower the sidelobe. These narrow sidelobes correspond to the overlap of continuous wave interference and C / A code spectral lines in the Doppler frequency dimension.

[0029] In some methods, when multiple multi-tone continuous wave interferences of different frequencies exist, the power of the interference signal can be divided into several continuous waves of different frequencies according to frequency. The power of each continuous wave is less than that of single-tone continuous wave interference, thus having a smaller destructive impact on the acquisition process. The contribution of multi-tone continuous wave interference to the correlation output can be expressed as: (5) Where, Δ f 1≠Δ f 2, C k1 ≠ C k2 ,A int1 , A int2 The amplitudes of the interference signals at the first and second frequencies are respectively. C k1 For the first k1 Each spectral line coefficient represents the coupling strength between the frequency of the interfering signal at the first frequency and the nearest C / A code spectral line. C k2 For the first k2 Each spectral line coefficient represents the coupling strength between the frequency of the interference signal at the second frequency and the nearest C / A code spectral line. , It can be calculated using formula (3).

[0030] S103: Construct a signal space based on the correlation value; wherein the signal space includes multiple cells formed with the Doppler frequency as the first dimension and the code phase delay as the second dimension, and the value of each cell is the correlation value corresponding to the Doppler frequency in the first dimension and the code phase delay in the second dimension; In this embodiment, the correlation values ​​obtained through relevant calculations include the correlation values ​​of all possible combinations of Doppler frequency and code phase delay. Based on this, a signal space composed of multiple units is constructed with Doppler frequency as the first dimension and code phase delay as the second dimension. The value of each unit is a correlation value uniquely determined by the Doppler frequency of the unit in the first dimension and the code phase delay of the unit in the second dimension.

[0031] For example, a signal space consisting of several units can be constructed with Doppler frequencies as rows and code phase delays as columns. Units in the same row have the same Doppler frequency but different code phase delays; units in the same column have different Doppler frequencies but the same code phase delay. For the unit in the m-th row and n-th column, its value is... Alternatively, a coordinate system can be established with code phase delay as the horizontal axis and Doppler frequency as the vertical axis. The value of the point at position (x, y) in the coordinate system is... The above methods for constructing the signal space are for illustrative purposes only, and this embodiment does not impose any specific limitations.

[0032] In some implementations, to search for a complete C / A code cycle, the receiver sampling frequency is 5.714 MHz. Within 1 ms, 5714 sampling points can be obtained. Each sampling point is used as a step to test all possible code phase alignments, meaning there are 5714 units to be searched in the code phase delay dimension. Within the Doppler spectrum range, for example, a Doppler spectrum range of ±7 kHz, the total frequency offset search range is 14 kHz. Within the integration time of 1 ms, all possible frequencies are searched in 100 Hz steps. The required search units are the total frequency offset search range divided by the spectral step plus 1, resulting in 141. That is, 141 units need to be constructed in the Doppler frequency dimension to cover all possible frequency offsets from -7 kHz to 7 kHz, ensuring that even with the maximum frequency offset, the signal can be found. Finally, a two-dimensional signal space with a code phase delay dimension of 5714 and a Doppler frequency dimension of 141 is constructed. This signal space consists of 5714×141 units, and the value of each unit is the correlation value under the corresponding code phase delay and Doppler frequency.

[0033] S104: Perform linear filtering on the correlation values ​​of the signal space to obtain the linearly filtered signal space; In this embodiment, considering that the received signal contains interference components, the correlation values ​​in the constructed signal space are affected by the interference signal, which is not conducive to capturing the useful signal. In order to filter out the interference components, the correlation values ​​in the signal space are subjected to linear filtering to enhance the useful satellite signal and suppress unnecessary continuous peaks.

[0034] In some embodiments, the correlation values ​​in the signal space are linearly filtered to obtain linearly filtered correlation values, including: For each cell in the signal space, determine the neighboring cells of that cell; By using a preset linear mask to perform a weighted summation with the cell and its neighboring cells, the correlation value of the cell after linear filtering is obtained.

[0035] In this embodiment, the correlation values ​​of a preset linear mask and the units in the signal space are weighted and summed to obtain the linearly filtered correlation value. Here, the linear mask, corresponding to a unit in the signal space, can be understood as multiple linear mask units with a mask radius. The value of each mask unit is a linear mask coefficient. The number of linear mask units is the same as the number of the current unit and its neighboring units in the signal space. For example, the number of linear mask units is 2n+1, and the total number of the current unit and its neighboring units is also 2n+1. Therefore, the correlation values ​​of the current unit and its neighboring units in the signal space are multiplied one-to-one with the linear mask coefficients of the linear mask units and then summed to obtain the linearly filtered correlation value of the current unit.

[0036] In some embodiments, for each cell in the signal space, determining the neighboring cells of that cell includes: For each cell of the same Doppler frequency in the first dimension, take the current cell as the center cell, and n cells forward and backward along the second dimension as the neighborhood cells. The correlation value of the current cell after linear filtering is obtained by weighted summation of the current cell and its neighboring cells using a preset linear mask. The method is as follows: (6) in, The correlation value is the result of linear filtering. For the first i The linear masking coefficients of a linear masking unit. The linear masking coefficients of the central linear masking unit. It can take the value 1 or 1.2; For code phase accuracy, n is the radius of the linear mask.

[0037] In this embodiment, during linear filtering, for each unit in the signal space, the neighborhood unit of that unit is defined as n units forward and n units backward along the second dimension, centered on that unit. This unit and its neighborhood units total (2n+1) units. Alternatively, if the Doppler frequency is used as the row and the code phase delay as the column, for the current unit in a row, the current unit is used as the center unit, and the n units forward and n units backward in that row are considered as neighborhood units. Correspondingly, the size of the linear mask is 1×(2n+1), meaning there are (2n+1) linear mask units in the same row. Figure 4 , 5 As shown, during linear filtering, for the current cell, the current cell and its neighboring cells are multiplied one-to-one with the linear mask cells, and then the multiplication results of the corresponding cells are added together to obtain the correlation value of the current cell after linear filtering.

[0038] Following this method, linear filtering is performed on each unit in the signal space sequentially. For example, for a signal space in the form of a matrix arranged in rows and columns, linear filtering can be performed on each unit in the first row from left to right, starting from the first unit in the first row at the top left corner. After the first row is finished, the units in the second row are filtered, and so on, until all units in the signal space have been linearly filtered.

[0039] In some approaches, for cells located at the edge of the signal space, only one linear mask cell can be used; for cells not located at the edge, additional linear mask cells can be used by setting... n The value of is used to flexibly select the number of neighboring units and choose appropriate linear mask units. nThe specific value is not limited, but the spatial size of the signal after linear filtering must remain unchanged.

[0040] The linear filter in this embodiment has a weak response to regions with uniform correlation values ​​within the linear mask, and enhances cells with significantly higher correlation values ​​than their neighbors, thereby highlighting discontinuities and weakening uniform correlation values.

[0041] S105: Based on the signal space after linear filtering, find the maximum correlation value under the same Doppler frequency and different code phase delay in the first dimension, calculate the sum of the distances between the maximum correlation value and each correlation value under the same Doppler frequency and other code phase delays, and select the maximum distance from the sum of the distances corresponding to each Doppler frequency. In this embodiment, considering that linear filtering cannot completely suppress clutter and may amplify discontinuities caused by noise, the global maximum peak in the signal space may be a spurious peak. This is because, through the characteristic analysis of interference signals, the peaks generated by interference generally appear in groups at the same Doppler frequency, while the peaks of satellite signals often exist in isolation at the Doppler frequency. That is, at the same Doppler frequency, a single peak may be a satellite signal, while multiple consecutive peaks may be interference signals. Therefore, only looking for the global maximum peak in the signal space while ignoring the distribution characteristics of the peaks may lead to the erroneous selection of an interference peak, making it impossible to accurately capture the signal.

[0042] To address this issue, considering the peak distribution characteristics of both interference and satellite signals, for each cell in the signal space with the same Doppler frequency and different code phase delays, an outlier point with the largest difference from other correlation values ​​is identified as the desired true satellite signal. This outlier's peak value may not be the global maximum peak value in the entire signal space, but rather a local peak value within the same Doppler frequency, exhibiting the largest difference from other correlation values ​​at the same Doppler frequency. Therefore, based on the linearly filtered signal space, the maximum distance is sought rather than the maximum correlation value.

[0043] In implementation, for each element at the same Doppler frequency, the maximum correlation value is found, represented as: (7) in, For the first i Doppler frequency f Di The maximum correlation value in each corresponding unit, that is, the maximum value among the correlation values ​​corresponding to the same Doppler frequency and different code phase delays. p This represents the amount of code phase delay.

[0044] The sum of the distances between the maximum correlation value corresponding to the same Doppler frequency and the correlation values ​​of other units at that Doppler frequency is calculated and expressed as: (8) Calculate the sum of distances corresponding to all Doppler frequencies using this method, and select the Doppler frequency corresponding to the maximum distance from the sum of distances corresponding to all Doppler frequencies. This is represented as: (9) in, q Given the number of Doppler frequencies, the desired Doppler frequency can be determined based on the selected maximum distance. f Dd The Doppler frequency is considered to be f Dd It is the Doppler frequency most likely to contain satellite signals.

[0045] S106: Perform nonlinear filtering on the correlation value of the Doppler frequency corresponding to the maximum distance to obtain the nonlinearly filtered correlation value; In this embodiment, after selecting the maximum distance, the Doppler frequency corresponding to the maximum distance is determined. f Dd The correlation values ​​of each unit corresponding to the Doppler frequency are further subjected to nonlinear filtering, and the presence of the target signal is determined based on the result of the filtering.

[0046] In some methods, the nonlinear filter utilizes a preset nonlinear mask and Doppler frequency. f Dd The correlation values ​​of each unit are filtered to obtain the nonlinear filtered correlation value. The nonlinear mask is determined based on the distribution characteristics of the interference signal and the satellite signal. The nonlinear mask consists of (2n'+1) nonlinear mask units, and the value of each nonlinear mask unit is determined according to a preset exponential function. The nonlinear mask units are used at the Doppler frequency... f Dd The algorithm slides up each cell and performs nonlinear filtering calculations on the covered cell region.

[0047] Based on the distribution characteristics of interference signals, interference occurs in clusters within the same Doppler frequency, while satellite signals exist in isolation within the same Doppler frequency. Therefore, when interference exists, the interference peaks within the cells covered by the nonlinear mask are similar, and the median correlation value of the covered cells is also close to the majority of interference peaks within the covered local cell region. In this case, the central cell covered by the nonlinear mask can be determined as noise and does not require sharpening filtering. If the correlation value of the central cell is much larger than the median correlation value of the covered cells, but there is an even larger correlation value at the same Doppler frequency, it can also be determined as noise. If the correlation value of the central cell is much larger than the median correlation value of the covered cells, and there is no larger correlation value at the same Doppler frequency, it can be determined as a valid peak value and requires maximum sharpening filtering. Thus, nonlinear filtering can effectively suppress noise and invalid peaks while enhancing valid peak values.

[0048] In some embodiments, the correlation value of the Doppler frequency corresponding to the maximum distance is subjected to nonlinear filtering to obtain the nonlinearly filtered correlation value. The method is as follows: (10) Where n' is the radius of the nonlinear mask; The correlation value is the result of nonlinear filtering. The nonlinear mask coefficients of the central nonlinear mask element. For the first i The nonlinear mask coefficients of each nonlinear mask element are calculated as follows: (11) in, S med is the median of the correlation values ​​of the cells covered by the nonlinear mask, and the nonlinear mask coefficient is greater than zero; C() is an exponential function that can return high values ​​for cell regions with drastic changes in correlation values ​​and low values ​​for cell regions with uniform correlation values, effectively distinguishing the peak values ​​of real satellite signals from the peak values ​​of interference signals.

[0049] In some methods, for each element corresponding to the same Doppler frequency, the number of elements in the sliding window can be flexibly selected by setting the value of n', and an appropriate nonlinear mask element can be selected. The specific value of n' is not limited, but it must be ensured that the number of elements after nonlinear filtering remains unchanged. For elements at the edge, their correlation value remains unchanged, or their correlation value is multiplied by a preset nonlinear mask coefficient to obtain a new correlation value.

[0050] In this embodiment, after determining the desired Doppler frequency, the correlation values ​​of each unit corresponding to the Doppler frequency are nonlinearly filtered using the provided nonlinear filter. Only the correlation values ​​corresponding to the real satellite signal that have significant differences are sharpened. At the same time, uniform peak values ​​caused by interference can be suppressed, so that the nonlinearly filtered signal is more conducive to identifying useful satellite signals.

[0051] S107: Determine whether the target signal exists based on the correlation value after nonlinear filtering.

[0052] In this embodiment, the correlation value after nonlinear filtering has effectively suppressed interference components and enhanced the satellite signal. Based on this, the Doppler frequency after nonlinear filtering... The maximum and second-largest correlation values ​​are selected from the corresponding units. The ratio of the maximum correlation value to the second-largest correlation value is calculated. This ratio is compared with a preset signal threshold. If the ratio is greater than the signal threshold, the signal corresponding to the maximum correlation value is determined to be a satellite signal.

[0053] The satellite receiver signal processing method provided in this application performs correlation operations on the received signal and then employs a two-stage filtering strategy. In the first stage, a linear filter with low computational complexity is used to reduce computational complexity and resource consumption. Subsequently, based on the statistical characteristic analysis of the interference signal and the satellite signal, the most likely Doppler frequency of the satellite signal is selected. The second stage of nonlinear filtering is performed only on the correlation values ​​corresponding to the selected Doppler frequency. While ensuring processing accuracy, this significantly improves the overall computational efficiency and meets real-time requirements. Nonlinear filtering can effectively suppress interference components and enhance satellite signal components. In the presence of interference signals, especially strong continuous wave interference signals, it can capture useful signals with high quality, improve robustness and anti-interference capability in strong interference environments, and does not rely on prior knowledge of interference signals. Its performance is stable and unaffected by errors.

[0054] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0055] It should be noted that the above description describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims may be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0056] like Figure 6 As shown in the illustration, this application also provides a satellite receiver signal processing apparatus, comprising: The demodulation module is used to demodulate the received satellite signals to obtain the baseband signal; The correlation calculation module is used to perform correlation calculations on the baseband signal and the local correlation sequence to obtain correlation values ​​for different Doppler frequencies and different code phase delays; The module is used to construct a signal space based on correlation values. The signal space includes multiple cells with Doppler frequency as the row and code phase delay as the column. The value of each cell is the correlation value corresponding to the Doppler frequency of the row and the code phase delay of the column. The linear filtering module is used to perform linear filtering on the correlation values ​​in the signal space to obtain the linearly filtered signal space. The lookup module is used to find the maximum correlation value in each row based on the linearly filtered signal space, calculate the sum of the distances between the maximum correlation value and the other correlation values ​​in the same row, and select the maximum distance from the sum of the distances corresponding to each row. The nonlinear filtering module is used to perform nonlinear filtering on the correlation values ​​of the row with the maximum distance to obtain the nonlinearly filtered correlation values. The capture module is used to determine whether a target signal exists based on the correlation value after nonlinear filtering.

[0057] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware.

[0058] The apparatus described above is used to implement the corresponding methods in the foregoing embodiments and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0059] Figure 7This embodiment illustrates a more specific hardware structure of an electronic device. The device may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0060] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0061] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0062] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0063] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0064] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0065] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0066] The electronic devices described above are used to implement the corresponding methods in the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0067] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0068] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this disclosure, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0069] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this disclosure, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0070] Although this disclosure has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0071] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this disclosure.

Claims

1. A method of signal processing for a satellite receiver, characterized by, The method comprises the following steps: demodulating a received signal to obtain a baseband signal; performing correlation calculation processing on the baseband signal and a local correlation sequence to obtain correlation values of different Doppler frequencies and different code phase delays; based on the correlation values, constructing a signal space; wherein the signal space comprises a plurality of units formed with Doppler frequency as the first dimension and code phase delay as the second dimension, and the value of each unit is the correlation value corresponding to the Doppler frequency in the first dimension and the code phase delay in the second dimension; performing linear filtering processing on the correlation values of the signal space to obtain a linearly filtered signal space; based on the linearly filtered signal space, finding the maximum correlation value under the same Doppler frequency and different code phase delays in the first dimension, calculating the sum of distances of the maximum correlation value and each correlation value under the same Doppler frequency and other code phase delays, and selecting the maximum distance from the sum of distances corresponding to each Doppler frequency; performing nonlinear filtering processing on the correlation value of the Doppler frequency corresponding to the maximum distance to obtain a nonlinearly filtered correlation value; based on the nonlinearly filtered correlation value, determining whether there is a target signal.

2. The method of claim 1, wherein, The linear filtering processing on the correlation values of the signal space comprises the following steps: for each unit of the signal space, determining the neighborhood units of the unit; performing weighted summation on the unit and its neighborhood units by using a preset linear mask to obtain the correlation value of the unit after linear filtering.

3. The method of claim 2, wherein, The determination of the neighborhood units of each unit of the signal space comprises the following steps: For each element at the same Doppler frequency in the first dimension, taking the current element as the central element, proceed forward and backward along the second dimension. n Each unit is considered a neighborhood unit; performing weighted summation on the current unit and its neighborhood units by using a preset linear mask to obtain the correlation value of the current unit after linear filtering. ； wherein, is a linear filtered correlation value, is a linear mask coefficient of the i-th linear mask unit, and i is a linear mask coefficient of the i-th linear mask unit, and is 1 or 1.2, is a code phase accuracy, is a code phase delay, f D is a Doppler frequency.

4. The method of claim 3, wherein, The nonlinear filtering processing on the correlation value of the Doppler frequency corresponding to the maximum distance comprises the following steps: performing filtering on the correlation values of each unit of the Doppler frequency corresponding to the maximum distance by using a preset nonlinear mask to obtain a nonlinearly filtered correlation value; wherein the nonlinear mask is determined according to the distribution characteristics of the interference signal and the satellite signal.

5. The method of claim 4, wherein, The nonlinear mask comprises a plurality of nonlinear mask units; the nonlinear filtering processing on the correlation value of the Doppler frequency corresponding to the maximum distance comprises the following steps: ； wherein, f Dd is the Doppler frequency corresponding to the maximum distance, is the correlation value after the nonlinear filtering, is the nonlinear mask coefficient of the center nonlinear mask unit, is the nonlinear mask coefficient of the th nonlinear mask unit, and the calculation method is: i is the nonlinear mask coefficient of the th nonlinear mask unit, and the calculation method is: ； wherein, S med Median of the correlation values for the cells covered by the non-linear mask.

6. A satellite receiver signal processing apparatus, characterized by The method comprises the following steps: a demodulation module for demodulating a received signal to obtain a baseband signal; a correlation calculation module for performing correlation calculation processing on the baseband signal and a local correlation sequence to obtain correlation values of different Doppler frequencies and different code phase delays; a construction module for constructing a signal space based on the correlation values; wherein the signal space comprises a plurality of units formed with Doppler frequency as the first dimension and code phase delay as the second dimension, and the value of each unit is the correlation value corresponding to the Doppler frequency in the first dimension and the code phase delay in the second dimension; a linear filtering module for performing linear filtering processing on the correlation values of the signal space to obtain a linearly filtered signal space; The searching module is configured to search, based on the linearly filtered signal space, a maximum correlation value at a same Doppler frequency and different code phase delays in the first dimension, calculate a sum of distances of the maximum correlation value and each correlation value at the same Doppler frequency and other code phase delays, and select a maximum distance from the sum of distances corresponding to each Doppler frequency. The nonlinear filtering module is configured to perform nonlinear filtering processing on the correlation value of the Doppler frequency corresponding to the maximum distance to obtain a nonlinearly filtered correlation value. The capturing module is configured to determine, based on the nonlinearly filtered correlation value, whether the target signal exists.

7. The apparatus of claim 6, wherein The linear filtering module is configured to determine, for each cell of the signal space, neighborhood cells of the cell, perform weighted summation on the cell and the neighborhood cells by using a preset linear mask to obtain a correlation value of the cell after linear filtering.

8. The apparatus of claim 7, wherein The linear filtering module is configured to, for each cell of the same Doppler frequency in the first dimension, take a current cell as a center cell and take n cells in front and back of the current cell along the second dimension as neighborhood cells. The linear filtering module is configured to perform weighted summation on the current cell and the neighborhood cells by using a preset linear mask to obtain a correlation value of the current cell after linear filtering. ； wherein, is a linear filtered correlation value, is a linear mask coefficient of the i-th linear mask unit, a linear mask coefficient of the center linear mask unit i is a linear mask coefficient of the i-th linear mask unit, a linear mask coefficient of the center linear mask unit is 1 or 1.2, is a code phase accuracy, is a code phase delay, f D is a Doppler frequency.

9. The apparatus of claim 8, wherein The nonlinear filtering module is configured to perform filtering on the correlation value of each cell of the Doppler frequency corresponding to the maximum distance by using a preset nonlinear mask to obtain a nonlinearly filtered correlation value, wherein the nonlinear mask is determined according to distribution characteristics of the interference signal and the satellite signal.

10. The apparatus of claim 9, wherein, The nonlinear mask includes a plurality of nonlinear mask cells. The nonlinear filtering module is configured to perform nonlinear filtering processing on the correlation value of the Doppler frequency corresponding to the maximum distance to obtain a nonlinearly filtered correlation value. ； wherein n' is the radius of the non-linear mask; f Dd is the Doppler frequency corresponding to the maximum distance, is the correlation value after non-linear filtering, is the non-linear mask coefficient of the central non-linear mask unit, is the non-linear mask coefficient of the first i non-linear mask unit, and the calculation method is: ； wherein, S med Median of the correlation values for the cells covered by the non-linear mask.

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