IFFT-based beam synthesis data reconstruction implementation method
By using the IFFT beamforming data reconstruction method, the problems of high resource consumption and inaccurate signal recovery in channelized transmitters are solved, achieving efficient signal recovery and resource conservation, and improving the accuracy of signal detection and module portability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NO 8511 RES INST OF CASIC
- Filing Date
- 2023-12-08
- Publication Date
- 2026-07-03
AI Technical Summary
Existing channelized transmitter architectures consume a lot of resources, and when the signal crosses multiple channels, harmonic components are introduced at the channel boundaries, resulting in poor coherence of the recovered signal. Spectral overlap leads to inaccurate time-domain signal recovery.
An IFFT-based beamforming data reconstruction method is adopted to restore signal coherence through signal sampling, decimation, interpolation, filtering, and spectrum shifting steps. This includes signal sampling, IFFT processing, low-pass filtering, and spectrum shifting, which reduces resource consumption, especially the multiplier resources of the FPGA chip.
It effectively restores the coherence of the original signal, reduces resource consumption, especially the multiplier resources of the FPGA chip, simplifies the design, and improves the accuracy and consistency of signal detection.
Smart Images
Figure CN117686977B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of radar technology, specifically a method for beamforming data reconstruction based on IFFT. Background Technology
[0002] Digital radio frequency (RF) memories modulate and forward received signals, effectively preserving signal coherence, and are widely used in radar technology. To improve system detection sensitivity, channelized detection technology has been widely applied to RF memory signal detection. The quality of signal recovery by the channelized transmitter directly affects the performance of the RF memory.
[0003] Currently, the multi-filter channelized transmitter technology based on direct frequency shift optimization is relatively mature. However, this architecture uses a lot of resources, and when the signal crosses multiple channels, harmonic components are introduced at the channel boundaries, resulting in poor coherence of the output signal. Furthermore, due to spectral overlap, the recovered signal differs significantly from the actual signal in the time domain. Therefore, the frequency domain recovery method is used to recover the time domain signal. Summary of the Invention
[0004] This invention proposes a beamforming data reconstruction method based on IFFT, which solves the problems of channelized transmitter architecture requiring more resources and the distortion of the recovered signal at the channel boundary when the signal crosses multiple channels, resulting in poor coherence between the recovered signal and the original signal. This invention is simpler to implement, uses fewer resources, and can still maintain coherence between the recovered signal and the original signal when the signal crosses multiple channels.
[0005] The technical solution for implementing this invention is: a method for beamforming data reconstruction based on IFFT, comprising the following steps:
[0006] Step 1: Using sampling rate f s The signal is sampled to obtain the original signal, and then sampled at a sampling rate f. s The center frequency of the next generation is f c N-point channelized data (x0[k], x1[k], ... x i [k],…x N-1 [k]), where k represents time.
[0007] Step 2: Extract M-level values from the N-point channelized data generated in Step 1 to obtain the signal center frequency f. c Corresponding data point x i N / M points centered at [k] The data after M-fold extraction is processed by IFFT to obtain IFFT data.
[0008] Step 3: Perform M-fold interpolation on the IFFT data obtained in Step 2 to obtain the interpolated data.
[0009] Step 4: The interpolated data from Step 3 is filtered by a low-pass filter with parameters [0M / N 2M / N 1] to obtain filtered data.
[0010] Step 5: Combine the filtered data with... Multiplication completes the spectrum shift, yielding complete time-domain signal data, i.e., the recovered signal, thus achieving data reconstruction; where the shifted frequency... j represents an imaginary number.
[0011] Compared with the prior art, the significant advantages of this invention are:
[0012] (1) In the application of beamforming technology, it can recover the original signal well and is not affected by the overlap of polyphase filtering signals.
[0013] (2) Compared with time-domain beamforming, it saves more resources, especially the multiplier resources of FPGA chips, which can effectively reduce the design difficulty of beamforming detection technology. Attached Figure Description
[0014] Figure 1 A flowchart of a beamforming data reconstruction method based on IFFT.
[0015] Figure 2 Time-domain waveforms of the recovered signal and the original signal.
[0016] Figure 3 Enlarged view of the time-domain waveform details of the recovered signal and the original signal.
[0017] Figure 4 Spectrum diagrams of the recovered signal and the original signal.
[0018] Figure 5 Enlarged view of the spectrum details of the recovered signal and the original signal. Detailed Implementation
[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.
[0020] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.
[0021] The following section will further introduce the specific implementation method, as well as the technical difficulties and inventive points of this invention, using examples from this design.
[0022] Combination Figure 1 The present invention provides a method for beamforming data reconstruction based on IFFT, comprising the following steps:
[0023] Step 1: Using sampling rate f s The signal is sampled to obtain the original signal, and then sampled at a sampling rate f. s The center frequency of the next generation is f c N-point channelized data (x0[k], x1[k], ... x i [k],…x N-1 [k]), where k represents time k.
[0024] Step 2: Extract M-level values from the N-point channelized data generated in Step 1 to obtain the signal center frequency f. c Corresponding data point x i N / M points centered at [k] Perform IFFT processing.
[0025] Step 3: Perform M-fold interpolation on the data obtained in Step 2 to obtain the interpolated data.
[0026] Step 4: The interpolated data from Step 3 is filtered by a low-pass filter with parameters [0 M / N 2M / N 1] to obtain filtered data.
[0027] Step 5: Combine the filtered data from Step 4 with... Multiplication completes the spectrum shift, yielding complete time-domain signal data, i.e., the recovered signal, thus achieving data reconstruction; where the shifted frequency... j represents an imaginary number.
[0028] During verification, the recovered signal and the original signal are compared in the time domain waveform and frequency domain spectrum. At the same time, the correlation coefficient between the recovered signal and the original signal is calculated, and the correlation between the recovered signal and the original signal is verified based on the correlation coefficient.
[0029] The present invention will now be described in further detail with reference to the embodiments.
[0030] Example:
[0031] The beamforming data reconstruction method based on IFFT described in this invention comprises the following steps:
[0032] Step 1: At a sampling rate of 2.4 GHz, generate 256-point channelized data (x0[k], x1[k], ... x) with a center frequency of 310 MHz and a signal bandwidth of 20 MHz. 255 [k]).
[0033] Step 2: Impede the data generated in Step 1 by 16 times to obtain the data point x corresponding to the signal center frequency of 300MHz. 33 The 16 points centered at [k] {x 33 [k],x 34 [k],…x 40 [k],x 25 [k],…x 32 [k]} is processed by IFFT to obtain the time-domain decimation signal of the 300MHz signal point.
[0034] Step 3: Interpolate the data obtained in Step 2 by a factor of 16 to obtain the time-domain signal of the original signal length;
[0035] Step 4: The data from Step 3 is filtered through a low-pass filter with parameters [01 / 161 / 81] to recover the original time-domain signal, but the frequency difference is 33 / 256*2.4GHz.
[0036] Step 5: Combine the data from Step 4 with e j2π·33[1:256] / 256 Multiplication completes the spectrum shift, resulting in the recovered signal.
[0037] During verification, the recovered signal and the original signal are compared in the time domain waveform and frequency domain spectrum. At the same time, the correlation coefficient between the recovered signal and the original signal is calculated to verify the correctness of the recovery and reconstruction method.
[0038] Combination Figure 3 The original signal bandwidth is 20MHz, the channelization bandwidth is 9.375MHz, and the original signal energy is distributed across three channels. Figure 2 , Figure 3 The recovered signal has a time-domain waveform that is basically the same as the original signal, with only a partial group delay.
[0039] This invention is the first to achieve time-domain signal recovery from beam-synthesized data in engineering, and the recovered signal is highly correlated with the original signal in the time domain, with a correlation coefficient of 0.9984, confirming that the recovered signal is coherent with the original signal. Figure 4 , Figure 5 It can be seen that the recovered signal and the original signal have basically the same main energy distribution in their spectra. The original signal spans three channels, and the recovered signal does not introduce spurious signals or harmonics at the channel boundaries. At the noise floor and where there is no signal, some spurious signals appear due to the decimation and interpolation process of the recovered signal, but the ratio of spurious power to peak power is less than -50dBc. Within a 1GHz bandwidth in the frequency domain, the frequency mean square error of the signal reconstruction method designed in this paper is less than 500kHz. This design method can effectively reduce chip resources such as multipliers, thereby reducing the development difficulty for software designers and improving module portability.
Claims
1. A method for beamforming data reconstruction based on IFFT, characterized in that, Includes the following steps: Step 1, sampling at a sampling rate f s The signal is sampled to obtain a raw signal, and N-point channelized data (x0[k], x1[k], … x i [k], … x N-1 [k]) with a center frequency f c is generated at a sampling rate f s , where k represents the time Step 2: Extract M-level values from the N-point channelized data generated in Step 1 to obtain the signal center frequency f. c Corresponding data point x i N / M points centered at [k] Perform IFFT processing on the data after M-fold extraction to obtain IFFT data; Step 3: Perform M-fold interpolation on the IFFT data obtained in Step 2 to obtain the interpolated data; Step 4: The interpolated data from Step 3 is filtered by a low-pass filter with parameters [0 M / N 2M / N 1] to obtain filtered data. Step 5: Combine the filtered data with... Multiplication completes the spectrum shift, yielding complete time-domain signal data, i.e., the recovered signal, thus achieving data reconstruction; where the shifted frequency... j represents an imaginary number.