A frequency offset estimation method and device, electronic equipment and storage medium

Abstract

This invention discloses a frequency offset estimation method, apparatus, electronic device, and storage medium, relating to the field of communication technology. The method includes: receiving a baseband spread spectrum signal from a low-Earth orbit satellite to obtain a received signal; performing segmented frequency sweep compensation on the received signal to obtain a compensated measured signal; using prior information determined from the received signal to despread and descramble the compensated measured signal, and performing a coarse frequency offset estimation on the measured signal after the first despreading and descrambling; performing a second despreading and descrambling on the signal data after the coarse frequency offset estimation, and performing a fine frequency offset estimation on the signal data after the second despreading and descrambling. This invention introduces prior information to directly lock and track a specified target beam signal, significantly improving the directionality and efficiency of the measurement; by designing a low-complexity signal processing flow, it can significantly reduce the algorithm burden, ensuring rapid completion of neighboring satellite beam frequency offset estimation during service operation, meeting the real-time requirements of seamless handover.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a frequency offset estimation method, apparatus, electronic device, and storage medium. Background Technology

[0002] In low-Earth orbit satellite communication systems, user terminals face frequent inter-satellite handovers. To ensure call quality during seamless handovers, terminals need to maintain existing service connections while accurately measuring the signal strength of neighboring satellite target beams pre-specified by the network side. This measurement accuracy directly depends on the high-precision estimation of the time-frequency offset of the neighboring satellite beam signals.

[0003] Existing estimation algorithms for high-dynamic, high-frequency-off scenarios are mainly designed for the initial beam search stage. However, they have significant shortcomings when applied to neighboring satellite beam measurement scenarios. Firstly, they lack target directionality. Existing methods aim to search for peak beams and cannot directly estimate the directionality of neighboring satellite beams specified by the network side, making it difficult to meet the accuracy requirements of neighboring satellite beam selection. Secondly, there is a mismatch between real-time performance and complexity constraints. Neighboring satellite beam measurement needs to be completed quickly while performing business operations, which places strict requirements on algorithm complexity. However, existing initial search algorithms usually pursue high acquisition probability and lack optimization for real-time performance and low complexity, making it difficult to adapt to the stringent requirements of switching scenarios. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the existing frequency offset signal estimation algorithm, which cannot be directly applied to inter-satellite beam switching, and to provide a frequency offset estimation method, device, electronic device, and storage medium.

[0005] The present invention solves the above-mentioned technical problems through the following technical solution:

[0006] Firstly, a frequency offset estimation method is provided for application in electronic devices; the frequency offset estimation method includes:

[0007] The baseband spread spectrum signal from a low-Earth orbit satellite is received to obtain the received signal; the received signal is then subjected to segmented frequency sweep compensation to obtain the compensated measured signal.

[0008] The compensated test signal is despread and descrambled using prior information determined from the received signal, and a coarse frequency offset estimate is performed on the received signal after the first despread and descramble.

[0009] The signal data after coarse frequency offset estimation is despread and descrambled again, and the fine frequency offset estimation is completed on the signal data after the second despread and descrambled process.

[0010] Secondly, a frequency offset estimation device is provided for use in electronic devices; the combined pilot large frequency offset estimation device includes:

[0011] The measured signal acquisition module is used to receive baseband spread spectrum signals from low-orbit satellites, obtain the received signal, and perform segmented frequency sweep compensation on the received signal to obtain the compensated measured signal.

[0012] The first frequency offset estimation module uses prior information determined from the received signal to despread and descramble the compensated test signal, and performs coarse frequency offset estimation on the test signal after the first despread and descramble.

[0013] The second frequency offset estimation module despreads and descrambles the signal data after coarse frequency offset estimation, and then performs fine frequency offset estimation on the signal data after the second despreading and descrambling.

[0014] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the methods described above.

[0015] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements any of the methods described above.

[0016] The positive and progressive effects of this invention are as follows:

[0017] This invention proposes a frequency offset estimation scheme for neighboring satellite beams in low-Earth orbit (LEO) satellites. It effectively addresses the core challenge of rapidly estimating large frequency offsets of a designated target beam under concurrent service conditions and low complexity constraints during neighboring satellite beam switching scenarios. On one hand, it introduces prior information based on network-side indications to directly lock and track the designated target beam signal, significantly improving the directionality and efficiency of the measurement and achieving an effective scenario-driven target locking mechanism. On the other hand, by designing a low-complexity signal processing flow and employing step-by-step frequency offset estimation and partial despreading and descrambling strategies, a lightweight parallel processing architecture is built. This significantly reduces the algorithmic burden, ensuring rapid neighboring satellite beam frequency offset estimation during service operation and meeting the real-time requirements of seamless switching. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the structure of a ground-orbit satellite communication system provided as an exemplary embodiment of the present invention.

[0019] Figure 2 A flowchart of a frequency offset estimation method provided as an exemplary embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of a frequency offset estimation device provided as an exemplary embodiment of the present invention.

[0021] Figure 4 A schematic diagram of simulation results provided for an exemplary embodiment of the present invention.

[0022] Figure 5 This is a schematic diagram of another simulation result provided for an exemplary embodiment of the present invention.

[0023] Figure 6 A schematic diagram of the simulation results of the detection probability comparison provided by an exemplary embodiment of the present invention.

[0024] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an example embodiment of the present invention. Detailed Implementation

[0025] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein.

[0026] Figure 1 A schematic diagram of a low-Earth orbit satellite communication system provided as an exemplary embodiment of the present invention is shown below. Figure 1 The low-orbit satellite spread spectrum communication system 1 includes a low-orbit satellite 11 and at least one mobile terminal (User Equipment, UE) 12.

[0027] In a preferred embodiment, the mobile terminal 12 may be, but is not limited to, a mobile phone, a tablet computer, a computer, a vehicle central control unit, or other similar devices. The number of mobile terminals 12 is not limited to the three shown in the figure; it may also be four, five, or even more.

[0028] Figure 2 The flowchart illustrates a frequency offset estimation method provided as an exemplary embodiment of the present invention, particularly a large frequency offset estimation method applicable to high dynamic, large frequency offset scenarios.

[0029] The following is combined with Figure 2 The process of this frequency offset estimation method is described in detail. The method may include the following steps:

[0030] Step 101: Receive the spread-spectrum baseband signal transmitted from a low-Earth orbit satellite to obtain the received signal. .

[0031] In a low-Earth orbit satellite spread spectrum communication scenario, assuming the received signal of mobile terminal 12 is... And if the received signal has completed the timing, then:

[0032] (1)

[0033] in, Indicates the carrier frequency. Indicates the initial frequency offset. Indicates the initial phase, and n represents the sequence index. Indicates the rate of change of Doppler frequency deviation. This represents additive white Gaussian noise. This indicates a baseband spread spectrum signal.

[0034] In low-Earth orbit (LEO) satellite spread spectrum communication systems, when a hybrid coding scheme of OVSF orthogonal spreading code + scrambling code is adopted, the baseband spread spectrum signal transmitted by the LEO satellite is spread... The mathematical representation is as follows:

[0035] (2)

[0036] in This indicates a satellite-specific scrambling code used to distinguish satellites. Indicates the spreading code of the CPICH channel. This indicates the spread spectrum of other channels, used to distinguish between them; This indicates a CPICH pilot signal, which is a sequence of all 1s with a power percentage of <10%. This indicates the signal of other channels; K represents the number of channels other than the CPICH channel.

[0037] Assuming the down-conversion signal frequency is Then receive the signal After complex phase downconversion to a zero intermediate frequency signal, it can be represented as:

[0038] (3)

[0039] in, This indicates the residual frequency offset of the down-conversion; in the case of low-Earth orbit satellites, this residual frequency offset can reach tens of kHz. ,visible With downconversion signal They are statistically uncorrelated, therefore It remains additive white Gaussian noise.

[0040] Compared to traditional methods where the spreading code and scrambling code are unknown during the initial blind search phase, in this embodiment of the invention, when the mobile terminal 12 reaches the conditions for beam measurement, the mobile terminal 12 has already known the spreading code and scrambling code of the target beam through network-side signaling. Therefore, this embodiment utilizes these two prior information to perform subsequent two-step orientation estimation.

[0041] Step 102: Divide the frequency offset range into multiple segments, and perform frequency sweep compensation on the received signal segment by segment to obtain the compensated test signal. .

[0042] Assuming the frequency offset range is First, the frequency offset range is divided into M segments, and the frequency offset interval of each segment is... For each frequency point for:

[0043] (4)

[0044] For the received signal After entering the i-th frequency sweep module, it can be represented as:

[0045] (5)

[0046] It should be noted that the value of M is determined based on the actual calculation requirements for despreading and descrambling. As an exemplary embodiment, if the frequency offset range is [-15kHz, 15kHz], the frequency offset range can be divided into 6 segments, with each segment having a frequency offset interval of 6kHz.

[0047] Step 103: Use the prior information obtained from the received signal to despread and descramble the compensated test signal.

[0048] This embodiment introduces prior information based on network-side indications to directly lock onto and track a specified target beam signal. By despreading and descrambling the measured signal after compensation based on prior information, directional acquisition is achieved, and spreading gain is obtained. The processing gain can be improved. dB.

[0049] In a preferred embodiment, the prior information obtained from the received signal includes at least the scrambling code and spreading code of the target beam.

[0050] As a preferred embodiment, the despreading and descrambling calculation of the measured signal is shown in the following formula:

[0051] (6)

[0052] in, * ( ) indicates conjugate. Indicates the length of the scrambling code. Indicates the length of the spreading code.

[0053] Step 104: Perform coarse frequency offset estimation on the measured signal after the first despreading and descrambling by coherent accumulation and peak search.

[0054] Specifically, this includes performing incoherent accumulation on the measured signal after the first despreading and descrambling, to obtain:

[0055] (7)

[0056] When the signal-to-noise ratio reaches its maximum, the frequency point can be considered as... Approaching the residual frequency deviation of the downconversion At this point, peak detection can be performed, and the frequency offset corresponding to the maximum peak value is the coarse frequency offset estimate. :

[0057] (8)

[0058] Thus, the first frequency offset estimation is completed for the despread and descrambled measured signal through coherent accumulation and peak search.

[0059] Step 105: Despread and descramble the signal data after coarse frequency offset estimation, and then perform fine frequency offset estimation.

[0060] Specifically, the signal data after coarse frequency offset estimation is first despreaded and descrambled again, as shown in the following equation:

[0061] (9)

[0062] Then, the precise frequency offset of the measured signal can be calculated using the partially matched filter-fast Fourier transform (PMF-FFT) method, as shown in the following formula:

[0063] , x≤n / λ(10)

[0064] in, This represents the signal after coarse frequency offset compensation. represents the sliding window step size, and x represents the number of sliding window points.

[0065] In this embodiment of the invention, by performing two despreading and descrambling calculations and two frequency offset estimations on the compensated signal data, the computational complexity can be reduced while estimating the frequency offset more sensitively and accurately, thus meeting the real-time requirements and accuracy requirements of concurrent services in neighboring satellite beam measurements.

[0066] While the joint pilot large frequency offset estimation method based on prior information provided in the aforementioned embodiments can already meet the seamless switching of low-orbit satellite communication under the spread spectrum system, considering that in practical applications, performing complete full-frame despreading and descrambling on the data to be processed with a length of X requires certain hardware resources to store the data to be processed; if the data to be processed is not stored and is directly despreaded and descrambled in real time, more computing units will be required and the hardware cost will be higher.

[0067] Furthermore, in the aforementioned embodiments, a full-frame despreading and descrambling operation of the complete spread spectrum frame length is required for each frequency offset segment under test during the secondary estimation stage. This process consumes a significant amount of correlator hardware resources and storage units, leading to increased chip area and power consumption, which is extremely detrimental to the hardware cost and control of the terminal device.

[0068] Assume N is the total length of the scrambling sequence (full frame length). Let OVSF code be the length (i.e., the spreading factor). Then, the quantitative relationship between the number of complete spreading code periods contained in a complete scrambling code period is as follows:

[0069] (11)

[0070] The above equation shows that the spreading code will repeat periodically within a complete scrambling cycle. Second-rate.

[0071] Therefore, this embodiment can further improve the aforementioned embodiment scheme by proposing a partial despreading and descrambling method, which improves the full-frame despreading and descrambling calculation of the first and / or second despreading and descrambling to partial despreading and descrambling, such as... Figure 2 As shown.

[0072] This despreading and descrambling method does not process the entire scrambling code period, but only selects a local sequence of length P for correlation calculation. Specifically, after frequency scanning, using the known scrambling code and spreading code, despreading and descrambling is performed only on the first P chips of each segment of the received signal, rather than the entire spreading frame. Then, the despreading and descrambling data of each segment is further subjected to coarse and fine frequency offset estimation. The corresponding partial despreading and descrambling calculations are as follows:

[0073] (12)

[0074] Where N is the total length of the scrambling sequence (i.e., the full frame length). The length of the local scrambling code actually used for partial despreading and descrambling. The length of the spreading code (i.e., the spreading factor).

[0075] According to the WCDMA standard, scrambling codes themselves do not possess orthogonality; their main function is to distinguish different cells or users. In a preferred embodiment, however, OVSF codes are used for spreading, which possess strict orthogonality under perfect synchronization conditions. This is the foundation for achieving interference-free transmission between channels.

[0076] To ensure that sufficient processing gain and anti-interference capability are retained after partial despreading and descrambling signal processing, and to avoid the loss of geodesic orthogonality of the spreading code due to excessively short processing length, the selection of the local scrambling code length P must meet the following key constraints:

[0077] (13)

[0078] when At this point, the length of the partial despreading and descrambling process is equal to the entire scrambling code period, which is equivalent to the full-frame despreading and descrambling scheme. This is the performance upper limit benchmark.

[0079] when This means that the length of the partial despreading and descrambling process must cover at least one complete spreading code period. This ensures that, under the premise of synchronization, the despreading and descrambling operation on the target pilot signal (such as CPICH) can utilize the orthogonality of the spreading code to effectively suppress interference from other channels and ensure the signal-to-noise ratio of the output signal.

[0080] when At this point, the length of some despreading and descrambling processes is shorter than one spreading code period, which disrupts the structure required for the complete correlation operation of the OVSF code, and its orthogonality cannot be maintained. This will lead to a severe deterioration in the signal-to-interference-plus-noise ratio (SINR) of the despreading and descrambling output signal, causing a sharp decline in subsequent synchronization and estimation performance, and rendering the scheme ineffective.

[0081] Therefore, in practical applications, the specific requirements of the system regarding performance, complexity, and cost can be considered when making choices. Under the given conditions, the optimal local processing length P is selected.

[0082] The optimized partial despreading and descrambling calculation scheme no longer requires storing pilot signals, which can significantly reduce algorithm complexity and hardware resource consumption, while accelerating synchronous acquisition with shorter data accumulation time.

[0083] Corresponding to the aforementioned embodiment of the frequency offset estimation method based on prior information for joint pilots, the present invention also provides an embodiment of a frequency offset estimation device.

[0084] Figure 3 A schematic diagram of a frequency offset estimation device 30 provided as an exemplary embodiment of the present invention is shown. The frequency offset estimation device 30 includes:

[0085] The measured signal acquisition module 31 is used to receive baseband spread spectrum signals from low-orbit satellites, obtain the received signals, and perform segmented frequency sweep compensation on the received signals to obtain the compensated measured signals.

[0086] The first frequency offset estimation module 32 is used to despread and descramble the compensated test signal using prior information determined from the received signal, and to perform coarse frequency offset estimation on the test signal after the first despread and descramble.

[0087] The second frequency offset estimation module 33 is used to despread and descramble the signal data after coarse frequency offset estimation again, and to complete the fine frequency offset estimation of the signal data after the second despread and descramble.

[0088] Optionally, the prior information determined from the received signal includes at least the spreading code and the scrambling code.

[0089] Optionally, the first frequency offset estimation module 32 and / or the second frequency offset estimation module 33 can be further used to partially despread and descramble the signal to be processed.

[0090] For the apparatus embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The apparatus embodiments described above are merely illustrative, and the modules described as separate modules may or may not be physically separate. Some or all of the modules can be selected to achieve the purpose of the present invention according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0091] Figures 4-6 This is a schematic diagram illustrating the simulation results based on the frequency offset estimation scheme provided in the aforementioned embodiments. The simulation test signal is a WCDMA signal constructed according to the 3GPP protocol, with a sampling rate of 3.84 Msps. The code channels include the Synchronization Channel (SCH), the Main Common Control Channel (P-CCPCH), and the Common Pilot Channel (CPICH), with added Gaussian white noise E0. c / N0 take The CPICH pilot channel has a spreading factor of 256, a carrier frequency offset of -27.5 kHz, and a frequency offset rate of change (Doppler acceleration) of 200 Hz / s.

[0092] like Figure 4 The diagram shows the results of the secondary frequency offset estimation based on full-frame despreading and descrambling. The full-frame despreading and descrambling algorithm exhibits significant peaks at both -30 kHz and -25 kHz. Due to its longer processing time and more complete correlation integration, this algorithm achieves higher processing gain and stronger anti-interference capability. Therefore, for adjacent scan frequencies (-30 kHz and -25 kHz), the absolute value of the residual frequency offset is 2.5 kHz, resulting in sufficiently detectable correlation peaks.

[0093] Figure 5 This is a schematic diagram of the secondary frequency offset estimation results based on partial despreading and descrambling. It can be seen that the improved partial despreading and descrambling scheme of this invention produces a significant peak at the -30 kHz frequency point. This result is attributed to the fact that the frequency deviation from the sweep point of -30 kHz is minimized to only 2.5 kHz when the true frequency offset is -27.5 kHz. Compared with full-frame despreading and descrambling, partial despreading and descrambling can still produce an effective correlation peak under this residual frequency difference, proving that this algorithm has superior acquisition capability.

[0094] However, for partial despreading and descrambling, theoretically, a peak should also appear at the symmetrical -25 kHz frequency point (with a deviation of 2.5 kHz). The absence of a significant peak at -25 kHz is fundamentally due to the fact that partial despreading and descrambling algorithms have relatively weaker anti-interference capabilities compared to full-frame despreading and descrambling algorithms. Under certain conditions, the influence of non-orthogonal interference (from other code channels) and noise reduces the output signal-to-interference-plus-noise ratio (SINR), causing the correlation peak at the symmetrical point to be submerged, thus failing to reach the detection threshold.

[0095] Further simulation testing showed a random initial frequency offset of [-30kHz, 30kHz], with a frequency offset change rate of 200Hz / s. The simulation results are as follows. Figure 6 As shown, the full-frame despreading and descrambling proposed in this embodiment of the invention has a detection probability greater than 99% when Ec / N0 is -24dB, while the partial despreading and descrambling has a detection probability greater than 99% when Ec / N0 is -22dB.

[0096] The complexity of the algorithm provided in the embodiments of the present invention is further analyzed.

[0097] First, we analyze the computational complexity of partial despreading and descrambling. The number of multiplication and addition operations required for partial despreading and descrambling at different frequency points is as follows: and (where y represents the computational complexity corresponding to the local scrambling code length), the multiplication and addition operations required for the squaring calculation are: and Then the number of multiplication and addition operations required to traverse all frequency points are respectively and Therefore, the overall computational complexity remains at [value missing]. The multiplication and addition operations required for full-frame despreading, descrambling, and summation are respectively... and (X represents the computational complexity corresponding to the complete spread frame length), the multiplication and addition operations for squaring are respectively... and Then the number of multiplication and addition operations required to traverse all frequency points are respectively and Therefore, the overall computational complexity of full-frame despreading and descrambling remains at [the required level]. The complexity of existing PMF-FFT algorithms is... .

[0098] Table 1 below compares the computational complexity of the two algorithms proposed in this invention with common large frequency offset estimation algorithms. The algorithm complexity relationships are as follows:

[0099] Traditional non-sweeping method < Partial despreading and descrambling algorithm < Full-frame despreading and descrambling algorithm < Traditional sweeping method.

[0100] It can be seen that the full-frame despreading and descrambling algorithm has a higher complexity, but it can achieve good performance under low signal-to-noise ratio conditions; while the partial despreading and descrambling algorithm has a lower complexity and slightly inferior performance, but it is more conducive to the implementation of practical applications.

[0101] Table 1. Comparison of the complexity of algorithms for frequency offset estimation of spread spectrum signals in low-Earth orbit satellite communication

[0102]

[0103] As can be seen, the two algorithms provided in this embodiment of the invention fully meet the high reliability, high sensitivity, and strong robustness requirements of inter-satellite handover in low-Earth orbit satellite communication under spread spectrum systems. Furthermore, the partial despreading and descrambling scheme achieves a significant reduction in computational complexity and hardware resource consumption by sacrificing some anti-interference performance (compared to more complex sliding correlation algorithms). Its successful capture at the main peak point verifies the effectiveness of the scheme, which is sufficient to meet the needs of many application scenarios. Compared to full-frame despreading and descrambling, the lack of peak symmetry in the partial despreading and descrambling algorithm directly reflects its performance trade-off in extremely low signal-to-noise ratio or strong interference environments. Therefore, in practical applications, the optimal choice between full-frame despreading and descrambling and partial despreading and descrambling can be made based on specific performance and complexity requirements.

[0104] Figure 7 This is a schematic diagram of the structure of a corresponding electronic device 70 shown in another embodiment of the present invention. Figure 7 The electronic device 70 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0105] like Figure 7 As shown, the electronic device 70 can be represented as a general-purpose computing device, such as a server device. The components of the electronic device 70 may include, but are not limited to: at least one processor 71, at least one memory 72, and a bus 73 connecting different system components (including memory 72 and processor 71). The bus 73 includes a data bus, an address bus, and a control bus.

[0106] The memory 72 may include volatile memory, such as random access memory (RAM) 721 and / or cache memory 722, and may further include read-only memory (ROM) 723.

[0107] The memory 72 may also include a program tool 725 having at least one program module 724, which includes, but is not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0108] The processor 71 performs various functional applications and data processing, such as the methods provided in any of the above embodiments, by running computer programs stored in the memory 72.

[0109] Electronic device 70 can also communicate with one or more external devices 74 (e.g., a keyboard). This communication can be performed via input / output (I / O) interface 75. The electronic device 70 corresponding to the model can also communicate with one or more networks via network adapter 76. As shown, network adapter 76 communicates with other modules of the model-generated electronic device 70 via bus 73. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated electronic device 70, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0110] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0111] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method provided in any of the above embodiments.

[0112] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A frequency offset estimation method, characterized in that, Applied to electronic devices; The frequency offset estimation method includes: The baseband spread spectrum signal from a low-Earth orbit satellite is received to obtain the received signal; the received signal is then subjected to segmented frequency sweep compensation to obtain the compensated measured signal. The compensated test signal is partially despread and descrambled using prior information determined from the received signal, and a coarse frequency offset estimate is performed on the test signal after the first despread and descramble. The prior information includes at least the spreading code and scrambling code of the target beam. The signal data after coarse frequency offset estimation is partially despread and descrambled again, and the fine frequency offset estimation is completed on the signal data after the second despread and descrambled process. The partial despreading and descrambling is used to despread and descramble a portion of the chips corresponding to the local scrambling code length; the local scrambling code length is not greater than the total length of the scrambling code sequence, and at the same time, the local scrambling code length is not less than the length of the spreading code.

2. The frequency offset estimation method according to claim 1, characterized in that, The process of receiving baseband spread spectrum signals from low-orbit satellites to obtain received signals also includes: converting the received signals into zero intermediate frequency signals through complex phase downconversion.

3. The frequency offset estimation method according to claim 1, characterized in that, By using frequency offset to perform segmented frequency sweep compensation on the received signal, the compensated measured signal is obtained, including: The frequency offset range is divided into different frequency bands, and the frequency offset interval of each band and the corresponding frequency point are determined. The received signal is divided into segments according to the frequency offset interval after the frequency band is divided and then entered into the frequency sweep module for frequency sweeping to obtain the compensated test signal.

4. The frequency offset estimation method according to claim 1, characterized in that, A coarse frequency offset estimation is performed on the measured signal after the first despreading and descrambling, including: Coarse frequency offset estimation is performed on the first despreading and descrambling of the measured signal by coherent accumulation and peak search.

5. The frequency offset estimation method according to claim 4, characterized in that, When the signal-to-noise ratio reaches its maximum, the frequency point is close to the residual frequency offset of the down-conversion. The peak value is detected, and the frequency offset corresponding to the maximum peak value is the coarse frequency offset estimate.

6. The frequency offset estimation method according to claim 1, characterized in that, The signal data after coarse frequency offset estimation is despread and descrambled again, and fine frequency offset estimation is performed on the signal data after the second despread and descrambled process, including: The signal data after coarse frequency offset estimation is despreaded and descrambled again; The precise frequency offset of the measured signal is calculated using the partially matched filter-fast Fourier transform method.

7. A frequency offset estimation device, characterized in that, Applied to electronic devices; The frequency offset estimation device includes: The measured signal acquisition module is used to receive baseband spread spectrum signals from low-orbit satellites, obtain the received signal, and perform segmented frequency sweep compensation on the received signal to obtain the compensated measured signal. The first frequency offset estimation module is used to partially despread and descramble the compensated test signal using prior information determined from the received signal, and to perform coarse frequency offset estimation on the received signal after the first despread and descramble; the prior information includes at least the spreading code and scrambling code of the target beam. The second frequency offset estimation module is used to perform partial despreading and descrambling on the signal data after coarse frequency offset estimation, and to complete fine frequency offset estimation on the signal data after the second despreading and descrambling. The partial despreading and descrambling is used to despread and descramble a portion of the chips corresponding to the local scrambling code length; the local scrambling code length is not greater than the total length of the scrambling code sequence, and at the same time, the local scrambling code length is not less than the length of the spreading code.

8. The frequency offset estimation device according to claim 7, characterized in that, The prior information determined from the received signal includes at least the spreading code and the scrambling code.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

Images