A weak signal receiving device based on Bayesian synchronization and signal enhancement

Abstract

The present invention discloses a weak signal receiving device based on Bayesian synchronization and signal enhancement, which relates to a highly reliable weak signal receiving device for long-distance wireless communications. The device comprises a receiving filter, a low-noise amplifier, a mixer, a receiving local oscillator, a bandpass filter amplifier, an analog-to-digital converter, a decimation filter, a Bayesian symbol synchronizer, an iterative resonance signal enhancer, and a channel decoder. The device utilizes Bayesian iterative symbol synchronization and iterative resonance signal enhancement techniques to demodulate received signals at low signal-to-noise ratios. This improves the receiver's synchronization and demodulation performance under low signal-to-noise ratio conditions, ensures error-free information transmission, and enhances the system's anti-interference capability. The device is particularly suitable for long-distance wireless communications such as deep space communications, satellite communications, and navigation communications.

Description

Technical Field

[0001] The invention discloses a weak signal receiving device based on Bayesian synchronization and signal enhancement, and relates to the field of weak signal reception in long-distance wireless communication. Background Art

[0002] To ensure highly reliable information transmission in long-distance wireless communications, such as deep space communications, satellite communications, and navigation communications, key technologies such as efficient coding and modulation methods and antenna arrays are required for error-free reception of weak signals. Due to the extremely low signal-to-noise ratio (SNR) of received signals, as the SNR decreases, the receiver's symbol synchronization and demodulation performance deteriorate, and decoding performance is not fully utilized, resulting in a decline in communication system performance. Summary of the Invention

[0003] The purpose of the present invention is to avoid the shortcomings of the above-mentioned background technology and provide a weak signal receiving device based on Bayesian synchronization and signal enhancement, which extracts symbol synchronization information and eliminates interference signals through time-frequency filtering and Bayesian iterative symbol synchronization technology; and performs low signal-to-noise ratio demodulation on the received signal through iterative resonance signal enhancement technology, thereby improving the synchronization and demodulation performance of the receiver under low signal-to-noise ratio, ensuring error-free transmission of information, and enhancing the system's anti-interference ability.

[0004] The technical solution adopted in the present invention is:

[0005] A weak signal receiving device based on Bayesian synchronization and signal enhancement, comprising a receiving filter 1, a low-noise amplifier 2, a mixer 3, a receiving local oscillator 4, a bandpass filter amplifier 5, an analog-to-digital converter 6, a decimation filter 7, and a channel decoder 10, and also comprising a Bayesian symbol synchronizer 8 and an iterative resonance signal enhancer 9;

[0006] The receiving filter 1 is used to filter the received signal, remove out-of-band noise and interference signals, and output the filtered signal to the low-noise amplifier 2;

[0007] The low noise amplifier 2 is used to perform low noise amplification on the filtered signal and output the amplified received signal to the mixer 3;

[0008] The mixer 3 is used to receive the amplified received signal from the low noise amplifier 2 and the received local oscillator signal from the received local oscillator 4, down-convert the amplified received signal, and output the down-converted signal to the bandpass filter amplifier 5;

[0009] The receiving local oscillator 4 is used to generate a receiving local oscillator signal and output it to the mixer 3;

[0010] The bandpass filter amplifier 5 is used to filter and amplify the down-converted signal, filter out out-of-band spurious and image signals, and output the processed intermediate frequency signal to the analog / digital converter 6;

[0011] The analog / digital converter 6 is used to perform analog / digital conversion on the intermediate frequency signal and output the converted sampled signal to the decimation filter 7;

[0012] The decimation filter 7 is used to perform clock conversion and decimation filtering on the sampled signal, and output the decimated digital baseband signal to the Bayesian symbol synchronizer 8 and the iterative resonance signal enhancer 9;

[0013] The Bayesian symbol synchronizer 8 is used to perform time-frequency filtering, pattern recognition, signal cyclic vector generation, discrete Fourier transform, Bayesian iteration and synchronization information extraction on the digital baseband signal, and then output the obtained pattern information and synchronization information to the iterative resonance signal enhancer 9;

[0014] The iterative resonance signal enhancer 9 is used to perform background noise preprocessing and iterative resonance signal enhancement processing on the digital baseband signal from the decimation filter 7 according to the mode information and synchronization information output by the Bayesian symbol synchronizer 8, and output the processed enhanced signal to the channel decoder 10;

[0015] The channel decoder 10 is used to perform efficient channel decoding on the enhanced signal output by the iterative resonance signal enhancer 9 to obtain decoded service information.

[0016] Furthermore, the Bayesian symbol synchronizer 8 includes a time-frequency filter 12, a signal pattern recognizer 13, a cyclic vector generator 14, a discrete Fourier transformer 15, a unilateral spectrum transformer 16, a Bayesian iterator 17, and a cyclic synchronization information extractor 18;

[0017] The time-frequency filter 12 is used to perform time-frequency filtering on the input digital baseband signal to eliminate interference signals, and output the de-interferenced signal to the signal pattern recognizer 13 and the cyclic vector generator 14;

[0018] The signal pattern recognizer 13 is used to perform pattern recognition on the signal after interference removal and output the obtained pattern information to the iterative resonance signal enhancer 9;

[0019] The cyclic vector generator 14 is used to perform cyclic autocorrelation statistics on the signal after interference removal, and output the cyclic autocorrelation vector of the signal to the discrete Fourier transformer 15;

[0020] The discrete Fourier transformer 15 is used to perform discrete Fourier transform on the cyclic autocorrelation vector from the cyclic vector generator 14, and output the transformed signal compression vector to the unilateral spectrum transformer 16;

[0021] The unilateral spectrum converter 16 is used to perform unilateral spectrum conversion processing on the signal compression vector input by the discrete Fourier transformer 15, and output the processed signal unilateral spectrum vector to the Bayesian iterator 17;

[0022] The Bayesian iterator 17 is used to perform Bayesian iteration on the unilateral spectrum vector of the signal from the unilateral spectrum converter 16 to obtain the periodic cycle vector of the signal and output it to the cycle synchronization information extractor 18;

[0023] The cycle synchronization information extractor 18 is used to extract symbol synchronization information from the periodic cycle vector from the Bayesian iterator 17 and output the obtained synchronization information to the iterative resonance signal enhancer 9.

[0024] Furthermore, the iterative resonance signal enhancer 9 includes a low-pass filter 19, a noise floor preprocessor 20, a vibration model selector 21, a threshold system 22, an iterative resonator 23 and an adaptive eye pattern output 24;

[0025] The low-pass filter 19 is used to perform group filtering on the digital baseband signal output by the decimation filter 7 and output the filtered signal to the noise floor preprocessor 20;

[0026] The noise preprocessor 20 is used to perform noise elimination processing on the filtered signal output by the low-pass filter 19, and output the noise-filtered signal to the iterative resonator 23;

[0027] The vibration model selector 21 is used to adaptively select a vibration model based on the pattern information and synchronization information from the Bayesian symbol synchronizer 8, and output the model parameter vector to the iterative resonator 23;

[0028] The threshold system 22 is used to generate a threshold information vector according to the pattern information from the Bayesian symbol synchronizer 8 and output the threshold information vector to the iterative resonator 23;

[0029] The iterative resonator 23 is used to generate an iterative resonance model based on the model parameter vector from the vibration model selector 21 and the threshold information vector from the threshold system 22, perform iterative resonance processing on the noise-filtered signal input by the noise floor preprocessor 20, and output the received eye diagram signal to the adaptive eye diagram output 24;

[0030] The adaptive eye pattern output 24 is used to perform adaptive amplitude adjustment on the received eye pattern signal from the iterative resonator 23 and output the processed enhanced signal to the channel decoder 10 .

[0031] Compared with the background technology, the present invention has the following advantages:

[0032] 1. The present invention adopts a Bayesian symbol synchronizer 8, uses time-frequency filtering technology to eliminate interference signals in the received signal, and adopts Bayesian iterative synchronization extraction technology to extract symbol synchronization information in the received signal under low signal-to-noise ratio, thereby improving the reliability of symbol synchronization and enhancing the anti-interference ability of the system.

[0033] 2. The present invention adopts an iterative resonance signal enhancer 9 and adopts iterative resonance signal enhancement technology to perform low signal-to-noise ratio demodulation on the received signal, which greatly improves the demodulation performance and optimizes the demodulation threshold by 2dB.

[0034] 3. The circuit components of the present invention are made of large-scale field programmable devices, so the operating parameters can be flexibly modified by configuring different programs, which greatly simplifies the structure of the equipment and significantly reduces the cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The present invention is a block diagram of the electrical principle of a weak signal receiving device based on Bayesian synchronization and signal enhancement.

[0036] Figure 2 1 is an electrical schematic diagram of an embodiment of the Bayesian symbol synchronizer 8 of the present invention.

[0037] Figure 3 1 is an electrical schematic diagram of an embodiment of an iterative resonance signal enhancer 9 of the present invention. DETAILED DESCRIPTION

[0038] The present invention will be further described in detail below with reference to the accompanying drawings.

[0039] Reference Figures 1 to 3 The present invention provides a weak signal receiving device based on Bayesian synchronization and signal enhancement, comprising a receiving filter 1, a low noise amplifier 2, a mixer 3, a receiving local oscillator 4, a bandpass filter amplifier 5, an analog / digital converter 6, a decimation filter 7, a Bayesian symbol synchronizer 8, an iterative resonance signal enhancer 9, a channel decoder 10, and a power supply 11. Figure 1 This is a block diagram of the electrical principle of a weak signal receiving device based on Bayesian synchronization and signal enhancement. Figure 1 Connect the lines.

[0040] The received signal of input port A is filtered by receiving filter 1 to remove out-of-band noise and interference signals, and the filtered signal is output to low-noise amplifier 2; low-noise amplifier 2 performs low-noise amplification on the filtered signal, and outputs the amplified received signal to mixer 3; mixer 3 receives the amplified received signal from low-noise amplifier 2 and the received local oscillator signal from receiving local oscillator 4, performs down-conversion processing on the amplified received signal, and outputs the down-converted signal to bandpass filter amplifier 5; receiving local oscillator 4 generates a received local oscillator signal and outputs it to mixer 3; bandpass filter amplifier 5 filters and amplifies the down-converted signal, filters out out-of-band spurious signals and image signals, and outputs the processed intermediate frequency signal to analog / digital converter 6; analog / digital converter 6 performs analog / digital conversion on the intermediate frequency signal, and outputs the converted sampled signal to decimation filter 7; decimation filter 7 performs analog / digital conversion on the intermediate frequency signal. The sampling signal is clock-converted and decimated and filtered, and the decimated digital baseband signal is output to the Bayesian symbol synchronizer 8 and the iterative resonance signal enhancer 9; the Bayesian symbol synchronizer 8 performs time-frequency filtering, pattern recognition, signal cyclic vector generation, discrete Fourier transform, Bayesian iteration and synchronization information extraction on the digital baseband signal, and then outputs the obtained pattern information and synchronization information to the iterative resonance signal enhancer 9; the iterative resonance signal enhancer 9 performs background noise preprocessing, iterative resonance signal enhancement and other processing on the digital baseband signal from the decimation filter 7 according to the pattern information and synchronization information output by the Bayesian symbol synchronizer 8, and outputs the processed enhanced signal to the channel decoder 10; the channel decoder 10 performs efficient channel decoding on the enhanced signal output by the iterative resonance signal enhancer 9, obtains the decoded service information and outputs it to the service output port B.

[0041] In this embodiment, the receiving filter 1 and low-noise amplifier 2 were fabricated using the YXLNA-2140 chip manufactured by Shijiazhuang Yuxun Electronics Co., Ltd. The mixer 3, receiving local oscillator 4, and bandpass filter amplifier 5 were fabricated using the IMZ0025B chip manufactured by the 13th Research Institute of China Electronics Technology Group Corporation. The analog-to-digital converter 6 was fabricated using the SAD9434EE chip manufactured by the 24th Research Institute of China Electronics Technology Group Corporation. The decimation filter 7, Bayesian symbol synchronizer 8, iterative resonance signal enhancer 9, and channel decoder 10 were all fabricated using the V7 series FPGA chips manufactured by Fudan Microelectronics Corporation.

[0042] The Bayesian symbol synchronizer 8 of the present invention performs time-frequency filtering, pattern recognition, signal cyclic vector generation, discrete Fourier transform, Bayesian iteration, and synchronization information extraction on the digital baseband signal, and then outputs the obtained pattern information and synchronization information to the iterative resonance signal enhancer 9. It consists of a time-frequency filter 12, a signal pattern recognizer 13, a cyclic vector generator 14, a discrete Fourier transform 15, a unilateral spectrum converter 16, a Bayesian iterator 17, and a cyclic synchronization information extractor 18. Figure 2Is the electrical schematic diagram of the Yes symbol synchronizer 8 of the present invention, the embodiment according to Figure 2 Connection line. The time-frequency filter 12 is used to perform time-frequency filtering on the input digital baseband signal to eliminate the interference signal, and output the de-interferenced signal to the signal pattern recognizer 13 and the cyclic vector generator 14; the signal pattern recognizer 13 performs pattern recognition on the de-interferenced signal and outputs the obtained signal pattern information to the iterative resonance signal enhancer 9; the cyclic vector generator 14 is used to perform cyclic autocorrelation statistics on the de-interferenced signal and output the cyclic autocorrelation vector of the signal to the discrete Fourier transformer 15; the discrete Fourier transformer 15 performs discrete Fourier transform on the cyclic autocorrelation vector from the cyclic vector generator 14, and transforms The resulting signal compression vector is output to a unilateral spectrum converter 16. Unilateral spectrum converter 16 performs unilateral spectrum conversion on the signal compression vector input from discrete Fourier transformer 15 and feeds the processed signal unilateral spectrum vector into a Bayesian iterator 17. Bayesian iterator 17 performs Bayesian iteration on the signal unilateral spectrum vector from unilateral spectrum converter 16 to obtain the signal's periodic cyclic vector and outputs it to a cyclic synchronization information extractor 18. Cyclic synchronization information extractor 18 extracts symbol synchronization information from the periodic cyclic vector from Bayesian iterator 17 and outputs the obtained synchronization information to an iterative resonance signal enhancer 9. The time-frequency filter 12, signal pattern recognizer 13, cyclic vector generator 14, discrete Fourier transformer 15, unilateral spectrum converter 16, Bayesian iterator 17, and cyclic synchronization information extractor 18 are all fabricated using V7 series FPGA chips produced by Fudan Microelectronics.

[0043] The iterative resonance signal enhancer 9 of the present invention performs noise preprocessing and iterative resonance signal enhancement on the digital baseband signal from the decimation filter 7 based on the pattern information and synchronization information output by the Bayesian symbol synchronizer 8, and outputs the enhanced signal to the channel decoder 10. It consists of a low-pass filter 19, a noise preprocessor 20, a vibration model selector 21, a threshold system 22, an iterative resonator 23, and an adaptive eye pattern output 24. Figure 3 This is the electrical schematic diagram of the iterative resonance signal enhancer 9 of the present invention. Figure 3The low-pass filter 19 is used to perform group filtering on the digital baseband signal output by the decimation filter 7 and output the filtered signal to the noise floor preprocessor 20. The noise floor preprocessor 20 performs noise floor elimination on the filtered signal output by the low-pass filter 19 and outputs the filtered signal to the iterative resonator 23. The vibration model selector 21 adaptively selects a vibration model based on the synchronization information and pattern information from the Bayesian symbol synchronizer 8 and outputs the model parameter vector to the iterative resonator 23. The threshold system 22 generates a threshold information vector based on the pattern information from the Bayesian symbol synchronizer 8 and outputs the threshold information vector to the iterative resonator 23. The iterative resonator 23 generates an iterative resonance model based on the model parameter vector from the vibration model selector 21 and the threshold information vector from the threshold system 22, performs iterative resonance processing on the filtered signal input by the noise floor preprocessor 20, and outputs a received eye diagram signal to the adaptive eye diagram output 24. The adaptive eye diagram output 24 adaptively adjusts the amplitude of the received eye diagram signal from the iterative resonator 23 and outputs the processed enhanced signal to the channel decoder 10. The low-pass filter 19, the background noise preprocessor 20, the vibration model selector 21, the threshold system 22, the iterative resonator 23 and the adaptive eye diagram output 24 are all made of the V7 series FPGA chip produced by Fudan Micro.

[0044] The power supply 11 of the present invention provides a DC operating voltage for the entire receiving device. The embodiment is made of a commercially available general-purpose integrated voltage-stabilized DC power supply module, and its output +V voltage is +5V.

[0045] The brief working principle of the weak signal receiving device based on Bayesian synchronization and signal enhancement of the present invention is as follows:

[0046] The received signal received at the input port A is filtered by the receiving filter 1 to remove out-of-band noise and interference signals, and the filtered signal is output to the low-noise amplifier 2; the low-noise amplifier 2 performs low-noise amplification on the filtered signal, and sends the amplified received signal to the mixer 3; the mixer 3 receives the amplified received signal from the low-noise amplifier 2 and the received local oscillator signal from the receiving local oscillator 4, performs down-conversion processing on the amplified received signal, and sends the down-converted signal to the bandpass filter amplifier 5; the receiving local oscillator 4 generates a received local oscillator signal and outputs it to the mixer 3; the bandpass filter amplifier 5 filters and amplifies the down-converted signal, filters out out-of-band spurious signals and image signals, and outputs the processed intermediate frequency signal to the analog / digital converter 6; the analog / digital converter 6 performs analog / digital conversion on the intermediate frequency signal, and outputs the converted sampled signal to the decimation filter 7; the decimation filter 7 The sampling signal is clock-converted and decimated and filtered, and the decimated digital baseband signal is output to the Bayesian symbol synchronizer 8 and the iterative resonance signal enhancer 9; the Bayesian symbol synchronizer 8 performs time-frequency filtering, pattern recognition, signal cyclic vector generation, discrete Fourier transform, Bayesian iteration and synchronization information extraction on the digital baseband signal, and then outputs the obtained pattern information and synchronization information to the iterative resonance signal enhancer 9; the iterative resonance signal enhancer 9 performs background noise preprocessing, iterative resonance signal enhancement and other processing on the digital baseband signal from the decimation filter 7 according to the pattern information and synchronization information output by the Bayesian symbol synchronizer 8, and sends the processed enhanced signal to the channel decoder 10; the channel decoder 10 performs efficient channel decoding on the enhanced signal output by the iterative resonance signal enhancer 9, obtains the decoded service information and outputs it to the service output port B.

[0047] The installation structure of the present invention is as follows:

[0048] The installation structure of the present invention is as follows: Figure 1 The receiving filter 1, low noise amplifier 2, mixer 3, receiving local oscillator 4, bandpass filter amplifier 5 and analog / digital converter 6 are installed on a printed circuit board with a size of 110×90mm in length and width; Figure 1 decimation filter 7, channel decoder 10 and Figure 2 、 Figure 3 All circuit components are installed on a printed circuit board with a size of 90×90 mm in length, width and height. Then, the two printed circuit boards are installed in a shielding box plug-in with a size of 130×100×60 mm in length, width and height. The front panel of the shielding box plug-in is installed with a cable socket connected to external ports A and B, and the rear panel is installed with a power input socket to assemble the present invention.

Claims

1. A weak signal receiving device based on Bayesian synchronization and signal enhancement, comprising a receiving filter (1), a low noise amplifier (2), a mixer (3), a receiving local oscillator (4), a bandpass filter amplifier (5), an analog / digital converter (6), a decimation filter (7) and a channel decoder (10), characterized in that: It also includes a Bayesian symbol synchronizer (8) and an iterative resonance signal enhancer (9); The receiving filter (1) is used to filter the received signal, remove out-of-band noise and interference signals, and output the filtered signal to the low-noise amplifier (2); The low noise amplifier (2) is used to perform low noise amplification on the filtered signal and output the amplified received signal to the mixer (3); The mixer (3) is used to receive the amplified received signal from the low noise amplifier (2) and the received local oscillator signal from the received local oscillator (4), perform down-conversion processing on the amplified received signal, and output the down-converted signal to the bandpass filter amplifier (5); The receiving local oscillator (4) is used to generate a receiving local oscillator signal and output it to the mixer (3); The bandpass filter amplifier (5) is used to filter and amplify the down-converted signal, filter out out-of-band spurious signals and image signals, and output the processed intermediate frequency signal to the analog / digital converter (6); The analog / digital converter (6) is used to perform analog / digital conversion on the intermediate frequency signal and output the converted sampling signal to the extraction filter (7); The decimation filter (7) is used to perform clock conversion and decimation filtering on the sampled signal, and output the decimated digital baseband signal to the Bayesian symbol synchronizer (8) and the iterative resonance signal enhancer (9); The Bayesian symbol synchronizer (8) is used to perform time-frequency filtering, pattern recognition, signal cyclic vector generation, discrete Fourier transform, Bayesian iteration and synchronization information extraction on the digital baseband signal, and output the obtained pattern information and synchronization information to the iterative resonance signal enhancer (9); The iterative resonance signal enhancer (9) is used to perform background noise preprocessing and iterative resonance signal enhancement processing on the digital baseband signal from the decimation filter (7) according to the pattern information and synchronization information output by the Bayesian symbol synchronizer (8), and output the processed enhanced signal to the channel decoder (10); The channel decoder (10) is used to perform efficient channel decoding on the enhanced signal output by the iterative resonance signal enhancer (9) to obtain decoded service information.

2. The weak signal receiving device based on Bayesian synchronization and signal enhancement according to claim 1, characterized in that: The Bayesian symbol synchronizer (8) includes a time-frequency filter (12), a signal pattern recognizer (13), a cyclic vector generator (14), a discrete Fourier transformer (15), a unilateral spectrum transformer (16), a Bayesian iterator (17) and a cyclic synchronization information extractor (18); The time-frequency filter (12) is used to perform time-frequency filtering on the input digital baseband signal to eliminate the interference signal, and output the de-interferenced signal to the signal pattern recognizer (13) and the circulant vector generator (14); The signal pattern recognizer (13) is used to perform pattern recognition on the signal after interference removal, and output the obtained pattern information to the iterative resonance signal enhancer (9); The cyclic vector generator (14) is used to perform cyclic autocorrelation statistics on the signal after interference removal, and output the cyclic autocorrelation vector of the signal to the discrete Fourier transformer (15); The discrete Fourier transformer (15) is used to perform discrete Fourier transform on the cyclic autocorrelation vector from the cyclic vector generator (14), and output the transformed signal compression vector to the unilateral spectrum transformer (16); The unilateral spectrum converter (16) is used to perform unilateral spectrum conversion processing on the signal compression vector input by the discrete Fourier converter (15), and output the processed signal unilateral spectrum vector to the Bayesian iterator (17); The Bayesian iterator (17) is used to perform Bayesian iteration on the unilateral spectrum vector of the signal from the unilateral spectrum converter (16), obtain the periodic cycle vector of the signal, and output it to the cycle synchronization information extractor (18); The cyclic synchronization information extractor (18) is used to extract symbol synchronization information from the periodic cyclic vector from the Bayesian iterator (17), and output the obtained synchronization information to the iterative resonance signal enhancer (9).

3. The weak signal receiving device based on Bayesian synchronization and signal enhancement according to claim 1, characterized in that: The iterative resonance signal enhancer (9) includes a low-pass filter (19), a noise floor preprocessor (20), a vibration model selector (21), a threshold system (22), an iterative resonator (23) and an adaptive eye diagram output (24); The low-pass filter (19) is used to perform group filtering on the digital baseband signal output by the decimation filter (7), and output the filtered signal to the noise floor preprocessor (20); The noise preprocessor (20) is used to perform noise elimination processing on the filtered signal output by the low-pass filter (19), and output the noise-filtered signal to the iterative resonator (23); The vibration model selector (21) is used to adaptively select a vibration model based on the pattern information and synchronization information from the Bayesian symbol synchronizer (8), and output the model parameter vector to the iterative resonator (23); The threshold system (22) is used to generate a threshold information vector according to the pattern information from the Bayesian symbol synchronizer (8), and output the threshold information vector to the iterative resonator (23); The iterative resonator (23) is used to generate an iterative resonance model based on the model parameter vector from the vibration model selector (21) and the threshold information vector from the threshold system (22), perform iterative resonance processing on the noise filtering signal sent by the background noise preprocessor (20), and output the received eye diagram signal to the adaptive eye diagram output (24); The adaptive eye diagram output (24) is used to perform adaptive amplitude adjustment on the received eye diagram signal from the iterative resonator (23), and output the processed enhanced signal to the channel decoder (10).

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