CN113050131A - Capturing method based on preprocessing FFT and barrier effect correction - Google Patents

Capturing method based on preprocessing FFT and barrier effect correction Download PDF

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CN113050131A
CN113050131A CN202110294207.4A CN202110294207A CN113050131A CN 113050131 A CN113050131 A CN 113050131A CN 202110294207 A CN202110294207 A CN 202110294207A CN 113050131 A CN113050131 A CN 113050131A
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frequency
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井俊
陈金权
李大鹏
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Nanjing University of Posts and Telecommunications
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
    • G01S19/29—Acquisition or tracking or demodulation of signals transmitted by the system carrier including Doppler, related
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/35—Constructional details or hardware or software details of the signal processing chain
    • G01S19/37—Hardware or software details of the signal processing chain
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03L—AUTOMATIC CONTROL, STARTING, SYNCHRONISATION, OR STABILISATION OF GENERATORS OF ELECTRONIC OSCILLATIONS OR PULSES
    • H03L7/00—Automatic control of frequency or phase; Synchronisation
    • H03L7/06—Automatic control of frequency or phase; Synchronisation using a reference signal applied to a frequency- or phase-locked loop
    • H03L7/08—Details of the phase-locked loop
    • H03L7/085—Details of the phase-locked loop concerning mainly the frequency- or phase-detection arrangement including the filtering or amplification of its output signal
    • H03L7/091—Details of the phase-locked loop concerning mainly the frequency- or phase-detection arrangement including the filtering or amplification of its output signal the phase or frequency detector using a sampling device

Abstract

The invention discloses a frequency capturing method based on preprocessing FFT and fence compensation, the work capturing probability of the method meets the requirement of deep space exploration, Doppler frequency estimation error caused by fence effect is eliminated, the locking of a tracking loop can be rapidly assisted, the modular design is realized, and the method has good adaptability to different signal dynamic ranges and capturing performance requirements. The deep space responder radio frequency module carries out down-conversion processing on a received carrier to obtain a zero intermediate frequency baseband signal, firstly carries out multi-branch rate matching on the received signal in a time domain, then calculates an FFT (fast Fourier transform) spectrum for each branch data and detects a power spectrum peak value, and obtains f according to a Doppler frequency branch where a global maximum value is located and a frequency rate branch0And the estimated value of a, the work capture probability can meet the deep space exploration requirement, and the Doppler frequency caused by the barrier effect is eliminatedThe doppler frequency estimation error can quickly assist the tracking loop to enter lock. The modularized design is realized, and the method has good adaptability to different signal dynamic ranges and acquisition performance requirements.

Description

Capturing method based on preprocessing FFT and barrier effect correction
Technical Field
The invention relates to a capture method based on preprocessing FFT and barrier effect correction, and belongs to the technical field of computers.
Background
The exploration of deep space is a leading action of human beings for expanding living space. The hot tide of deep space exploration in the world has been around for many years and has become more active in recent years. Mars, Venus, Mars, comets and asteroids in the United states, Europe and Japan are constantly getting new findings from the universe. The deep space exploration is to develop and utilize space resources, develop space technology, carry out scientific research, explore the origin of solar systems and universes, expand human living space and serve the long-term sustainable development of the human society. In deep space activities, a ground measurement and control communication system is an important component of the deep space activities, and the ground measurement and control communication system and a space transponder complete tracking, remote measurement, instruction control and data transmission of a deep space detector. However, in the whole flight process of the deep space probe, the deep space probe needs to be measured and controlled to ensure the accuracy of the flight track of the deep space probe, and after the deep space probe enters the detection process, detection information needs to be transmitted back, so that the deep space measurement and control communication system is the only information line for deep space detection, is very important and has more prominent importance than other measurement and control systems. For example: a phase interpretation method 201710355621.5 based on fast Fourier transform is disclosed, which adopts fast Fourier transform algorithm to interpret the phase difference between output signal and input signal at target frequency point, and improves the accuracy of phase interpretation of target frequency point by properly selecting and setting sampling frequency, input signal acquisition data and output signal acquisition data. However, the method cannot realize that the work capture probability meets the requirement of deep space exploration, cannot eliminate Doppler frequency estimation error caused by a barrier effect, and can quickly assist in tracking loop locking.
The current multi-branch time domain change rate matching FFT module value selection maximum algorithm realizes accurate estimation of signal parameters under the condition that the signal-to-noise ratio is-38 dB, but the algorithm requires high matching precision. The current time domain matching average periodogram algorithm weakens the requirement of Doppler change rate matching precision, reduces the complexity of single operation under the same dynamic condition, is more suitable for coarse carrier capture, but performs full FFT operation on all matching branches, increases the computation complexity in proportion along with the expansion of a dynamic range, and brings difficulty to the real-time carrier capture of deep space detection signals. In practical engineering application, an algorithm of preprocessing FFT is generally adopted, and in addition, the capture of deep space low signal-to-noise ratio high dynamic carrier needs to solve the following problems:
1) in engineering application, fast spectrum analysis is mainly carried out on carrier signals by adopting FFT (fast Fourier transform), and a spectrum peak value is found out to complete carrier capture. However, for a high dynamic deep space sounding carrier, a large doppler frequency change rate exists, a large frequency moves within a one-time FFT duration, carrier energy is dispersed to different frequencies, the pattern of an FFT spectrum peak is changed from a single peak point to multiple peak points, and the number of the peak points spans (f)0,f0+aTFFT) This interval, where f is such that the FFT acquisition algorithm no longer satisfies the maximum likelihood characteristic0Is the carrier frequency, a is the carrier frequency rate of change, TFFTIs the time of one FFT.
2) The FFT transformation results in discrete spectral lines whose frequency resolution limits the accuracy of the frequency acquisition, referred to as the "fence effect". The deep space communication has the characteristic of extremely low signal-to-noise ratio, the loop bandwidth of a high-order phase-locked loop after the carrier is captured roughly is very narrow, and the high-order phase-locked loop is very sensitive to the fence effect of an FFT spectral peak. In order to ensure that the transponder smoothly shifts from frequency acquisition to phase tracking, the barrier effect needs to be eliminated when the algorithm is designed.
3) And dividing the Doppler frequency range and the Doppler change rate range to be searched into squares during signal acquisition. The size setting of the search grid needs to consider the unknown doppler frequency and the range of doppler change rate, the signal-to-carrier-to-noise ratio, the acquisition time and the requirements of detection performance. The present invention can solve the above problems well.
Disclosure of Invention
The invention aims to provide a frequency acquisition method based on preprocessing FFT and fence compensation aiming at the problem of low signal-to-noise ratio high dynamic deep space carrier acquisition, the work acquisition probability of the method meets the deep space detection requirement, the Doppler frequency estimation error caused by the fence effect is eliminated, the loop locking can be quickly assisted and tracked, the modular design is well realized, and the method has good adaptability to different signal dynamic ranges and acquisition performance requirements.
The technical scheme adopted by the invention for solving the technical problems is as follows: frequency capturing method based on preprocessing FFT and fence compensationThe method comprises the steps that a deep space responder radio frequency module carries out down-conversion processing on a receiving carrier to obtain a zero intermediate frequency baseband signal, the receiving signal is subjected to multi-branch rate of change matching in a time domain, then FFT spectrums are obtained for data of all branches and power spectrum peak values are detected, and f is obtained according to a Doppler frequency branch where a global maximum value is located and a frequency rate branch0And an estimate of a.
The preprocessing FFT module makes the Doppler change rate of local oscillators of each matching branch uniformly distributed, and the Doppler change rate is a1,a2,a3,...,aM-1,aMAnd each matched difference frequency signal is expressed as:
Figure BDA0002983689320000031
wherein r isi(t) is the difference frequency signal after each path of matching, aiFor the doppler change rate of the local oscillator of each matching branch, i is 1,2,3i-ai-1For Doppler rate of change residual, riAnd (t) carrying out discretization and fast Fourier transform to obtain M-frame Fourier discrete spectrum. The square of the modulus of each frame for an N-point FFT is denoted as d i1,2, 3. For diTwo times of maximum value searching are carried out, firstly, a single-frame discrete spectrum d is searched and recordediMaximum spectral line value d ini1,2,3, M and its corresponding index value ki,ki＝1,2,3,...,N diI 1,2,3, M is the square of the modulus of the N-point FFT per frame. Second compare M numbers diAnd recording the k corresponding to the maximum valueiAnd i.
Figure BDA0002983689320000032
And
Figure BDA0002983689320000033
respectively corresponding to the captured Doppler frequency grid and Doppler change rate grid, ki, k i1,2,3, N is the maximum spectral line value diI 1,2,3, and M corresponds to an index value.
Has the advantages that:
1. the work capture probability of the invention can meet the deep space detection requirement, and the Doppler frequency estimation error caused by the fence effect is eliminated, thereby being capable of rapidly assisting the tracking loop to enter the lock.
2. The invention well realizes the modular design and has good adaptability to different signal dynamic ranges and acquisition performance requirements.
3. In deep space detection, the signal of the invention is characterized by low signal-to-noise ratio and high dynamic.
4. The preprocessing FFT module is responsible for searching a Doppler frequency domain and a Doppler change rate domain, and the FFT fence elimination module is responsible for further reducing the capture frequency error so as to facilitate the tracking of a narrow-band phase-locked loop.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a diagram of a pre-processing FFT module according to the present invention.
FIG. 3 is a diagram of Doppler ratio multi-branch/FFT two-dimensional search spectrum peak according to the present invention.
FIG. 4 is a diagram illustrating the estimation error of the fence effect frequency of DFT spectrum according to the present invention.
Fig. 5 is a diagram illustrating fence effect cancellation of FFT spectra.
Detailed Description
The invention is described in further detail below with reference to the drawings.
In a deep space measurement and control communication system, a radio frequency signal received by a receiving end is converted into an intermediate frequency signal which can be processed by a baseband after channel down-conversion, and the frequency components of the intermediate frequency signal comprise an intermediate frequency, a carrier frequency offset, a carrier frequency change rate and a higher order change rate thereof. During the signal acquisition phase, the input signal can be considered to be a Linear Frequency Modulation (LFM) signal, regardless of the rate of change of the carrier frequency in the second order and above. Now, the signal is analyzed by using a carrier frequency linear variation model, and the complex model signal is
Figure BDA0002983689320000041
Wherein: a is signal amplitude, and is taken as +/-1; f. of0+ at is the actual signal frequency (including carrier frequency offset); a is the carrier frequency rate of change;
Figure BDA0002983689320000042
for the initial phase, n (t) is additive gaussian noise. In deep space detection, signals often have the characteristics of low signal-to-noise ratio and high dynamics. The problem of signal acquisition is generally a signal parameter estimation problem, and the task of deep space communication carrier acquisition is to determine the carrier frequency and the frequency change rate of a received signal. At present, carrier coarse acquisition algorithms for extremely low signal-to-noise ratio and high dynamic signals are mainly classified into 3 types:
1) an algorithm is estimated based on Maximum Likelihood (ML) or improved ML criteria. Such algorithms start from a parameter estimation problem, and generally adopt a maximum likelihood estimation method, that is, a likelihood function is calculated:
Figure BDA0002983689320000051
where, (f ', a') is the carrier frequency and frequency change rate parameter of the received signal.
The parameter (f ', a') that maximizes L (f ', a') is found within the feasible region. Based on the additive gaussian noise property of n (t), the problem translates into:
Figure BDA0002983689320000052
maximum (f ', a'). The maximum likelihood estimation is a nonlinear optimization problem of multi-dimensional search, has high calculation complexity and high selection requirement on an initial value, and can hardly be applied in practice.
2) LFM signal detection based on a time-frequency analysis method. And performing time-frequency analysis by using tools such as Radon-Hilbert-Huang transform, Gabor-Radon transform and the like. The algorithm lacks a fast algorithm in practical application, and the cost of operation complexity is paid when higher sensitivity is obtained.
3) A Fast Fourier Transform (FFT) algorithm with preprocessing. After linear change of Doppler is eliminated through time domain serial or multi-branch parallel preprocessing, efficient Doppler frequency detection is carried out by utilizing an FFT algorithm.
As shown in fig. 1, the present invention provides a deep space sounding carrier capture algorithm based on pre-processing FFT and fence compensation, in which the pre-processing FFT module of the method is responsible for searching the doppler frequency domain and the doppler change rate domain, and the FFT fence elimination module is responsible for further reducing the capture frequency error, so as to facilitate tracking of the narrow-band phase-locked loop.
The preprocessing FFT module of the capture algorithm of the invention is shown in figure 2, and the deep space responder radio frequency module carries out down-conversion processing on the received carrier to obtain a zero intermediate frequency baseband signal. Firstly, carrying out multi-branch rate matching on a received signal in a time domain, then solving an FFT (fast Fourier transform) spectrum for each branch data and detecting a power spectrum peak value, and obtaining f according to a Doppler frequency branch where a global maximum value is located and a frequency rate branch0And an estimate of a.
The preprocessing FFT module makes the Doppler change rate of local oscillators of each matching branch uniformly distributed, and the Doppler change rate is a1,a2,a3,...,aM-1,aMAnd each matched difference frequency signal is expressed as:
Figure BDA0002983689320000061
wherein r isi(t) is the difference frequency signal after each path of matching, aiFor the doppler change rate of the local oscillator of each matching branch, i is 1,2,3i-ai-1For Doppler rate of change residual, riAnd (t) carrying out discretization and fast Fourier transform to obtain M-frame Fourier discrete spectrum. The square of the modulus of each frame for an N-point FFT is denoted as d i1,2, 3. For diTwo times of maximum value searching are carried out, firstly, a single-frame discrete spectrum d is searched and recordediMaximum spectral line value d ini1,2,3, M and its corresponding index value ki,ki＝1,2,3,...,N diI 1,2,3, M is the square of the modulus of the N-point FFT per frame. Second compare M numbers diAnd recording the k corresponding to the maximum valueiAnd i.
Figure BDA0002983689320000062
And
Figure BDA0002983689320000063
respectively corresponding to the captured Doppler frequency grid and Doppler change rate grid, ki, k i1,2,3, N is the maximum spectral line value diI 1,2,3, and M corresponds to an index value.
The invention aims at the Doppler frequency range and the Doppler change rate range of [ -100kHz and 100kHz respectively]And [ -100Hz/s,100Hz/s]Considering that the carrier-to-noise ratio is 15dBHz, the signal sampling time length corresponding to the number N of the FFT conversion points is set to be 0.25s, the detection signal-to-noise ratio of about 9dB can be obtained, and the frequency resolution is 4 Hz. The received signal is sampled at I, Q and the sampling rate fs240ksps, the acquisition range of the doppler frequency is [ -120kHz,120kHz]. By zero-filling the sequence to an integer multiple of 2 before FFT, higher doppler frequency resolution can be achieved. The invention carries out zero padding and integration on 60000 samples to obtain N65536 samples, and the FFT spectrum resolution is about 3.66 Hz. In order to enable the Doppler frequency to move less than 3.66Hz within the single FFT time length, the number of the Doppler change rate branches is set to be 26, and the branch distance is set to be 8 Hz/s.
The relative capture threshold is set to be 2 times of the noise variance, and the Doppler rate-Doppler two-dimensional search spectrum peak obtained by single simulation is shown in FIG. 3. The parameter setting of the preprocessing FFT part is shown in table 1, Monte Carlo simulation is carried out 5000 times for each situation, double judgment of absolute threshold and relative threshold is adopted to reduce false alarm probability, and capture probability under different carrier-to-noise ratio conditions is obtained through statistics. The statistical result shows that the Doppler change rate error is less than 4Hz/s, the Doppler estimation error is less than 2Hz, and the capture probability meets the requirement.
Table 1: two-dimensional capture monte carlo simulation condition presetting
Figure BDA0002983689320000071
When the algorithm is realized in the FPGA, a single FFT operation module works under the drive of a high-power clock, the spectral peaks of all M branches can be rapidly calculated, and the capture time is ensured to meet the requirement of deep space detection.
The resulting discrete spectrum of the FFT is a sample of the Sinc function whose peak is at the actual doppler frequency value, according to the discrete fourier transform rationale of the sequence. Due to the spectral dispersion characteristic of the FFT, only the spectral line amplitudes of discrete points can be seen, as if the spectrum were viewed through a barrier, referred to as the "barrier effect". Therefore, errors often exist between the maximum value of the discrete spectrum and the actual Doppler frequency during capturing, the fence elimination effect can ensure that the phase-locked loop can be rapidly captured, and the probability of losing the lock of the loop is reduced. As shown in fig. 4, when the FFT resolution is 3.66Hz, the maximum frequency estimation error can be up to half of the frequency resolution, i.e., 1.83 Hz.
The method of zero filling to the sequence and increasing the number of FFT points can be adopted to improve the barrier effect during the algorithm design, but the operation complexity can be multiplied, the amplitude information of the discrete spectral line is utilized to correct the barrier effect, and the frequency capture error caused by the barrier effect can be effectively reduced. When the FFT frequency acquisition is completed, the highest spectral line value A (k) in the discrete spectrum and the next highest spectral lines on two sides of the discrete spectrum are found and are marked as A (k-1), A (k + 1).
As shown in fig. 5, assuming that the offset between the a (k) spectral position and the true doppler frequency is δ, the discrete spectral amplitude is related to the position offset δ as defined by the function of Sinc:
Figure BDA0002983689320000081
where δ is the position offset, AspFor the true spectral peak, A (k) is the highest spectral line value in the discrete spectrum, AspWhich is the true spectral peak, is indicated by the dashed line in fig. 5 due to the fence effect.
If A (k-1) < A (k +1), then A (k +1) is closer to the true spectral peak, as follows:
Figure BDA0002983689320000082
the position deviation is represented by a discrete spectrum peak, and the method can be obtained
Figure BDA0002983689320000083
Wherein delta1The position deviation corresponding to A (k +1) is shown.
If A (k +1)<A (k-1), obtainable accordingly
Figure BDA0002983689320000084
Wherein delta-1The position offset corresponding to A (k-1).
And recording the position of a real spectral line as k', and correcting and calculating the position k of the maximum spectral line as follows to obtain an accurate Doppler frequency estimation result:
Figure BDA0002983689320000085
where k' is the true spectral line position and k is the maximum spectral line position.
The parts not involved in the present invention are the same as or can be implemented using the prior art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (3)

1. A frequency acquisition method based on preprocessing FFT and fence compensation is characterized in that the method is deepThe method comprises the steps that a radio frequency module of the air responder carries out down-conversion processing on a received carrier to obtain a zero intermediate frequency baseband signal, firstly, multi-branch change rate matching is carried out on the received signal in a time domain, then, an FFT (fast Fourier transform) spectrum is obtained for each branch data, a power spectrum peak value is detected, and f is obtained according to a Doppler frequency branch where a global maximum value is located and a frequency change rate branch0And an estimate of a.
2. The method according to claim 1, wherein the method comprises a pre-FFT module, and the pre-FFT module makes doppler change rates of local oscillators in each matching branch uniformly distributed, where a is a1,a2,a3,...,aM-1,aMAnd each matched difference frequency signal is expressed as:
Figure FDA0002983689310000011
wherein r isi(t) is the difference frequency signal after each path of matching, aiFor the doppler change rate of the local oscillator of each matching branch, i is 1,2,3i-ai-1For Doppler rate of change residual, ri(t) performing discretization and fast Fourier transform to obtain M frames of Fourier discrete spectrum, and recording the square of the N-point FFT modulus of each frame as di1,2,3,. M, for diTwo times of maximum value searching are carried out, firstly, a single-frame discrete spectrum d is searched and recordediMaximum spectral line value d ini1,2,3, M and its corresponding index value ki,ki＝1,2,3,...,N di1,2,3, M is the square of the modulus of the N-point FFT per frame, followed by a comparison of M diAnd recording the k corresponding to the maximum valueiAnd
Figure FDA0002983689310000012
and
Figure FDA0002983689310000013
respectively corresponding to the captured Doppler frequency grid and Doppler change rate grid, ki,ki1,2,3, N is the maximum spectral line value diI 1,2,3, and M corresponds to an index value.
3. The frequency acquisition method based on preprocessing FFT and fence compensation as claimed in claim 1, wherein the method comprises a deep space measurement and control communication system, in which a radio frequency signal received by a receiving end is converted into an intermediate frequency signal capable of being processed by a baseband after down-conversion by a channel, frequency components of the intermediate frequency signal include an intermediate frequency, a carrier frequency offset, a carrier frequency change rate and a higher order change rate thereof, and in a signal acquisition stage, if a change rate of a carrier frequency second order or above is not considered, an input signal is regarded as a Linear Frequency Modulation (LFM) signal, and a carrier frequency linear change model is used to analyze the signal, and complex model signals of the signal are:
Figure FDA0002983689310000021
wherein: a is signal amplitude, and is taken as +/-1; f. of0+ at is the actual signal frequency, including the carrier frequency offset, a is the carrier frequency change rate;
Figure FDA0002983689310000022
for the initial phase, n (t) is additive gaussian noise.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114244384A (en) * 2021-12-20 2022-03-25 浙江嘉科电子有限公司 Continuous wave peak value capturing circuit and method for zero intermediate frequency receiver

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104407323A (en) * 2014-12-11 2015-03-11 中国工程物理研究院电子工程研究所 Measuring method for pseudo code delay of spread spectrum signal with high dynamic range and low signal-to-noise ratio
CN109495410A (en) * 2018-09-28 2019-03-19 西南电子技术研究所（中国电子科技集团公司第十研究所） High dynamic PCM/FM signal(-) carrier frequency precise Estimation Method
CN110518936A (en) * 2019-07-22 2019-11-29 西安电子科技大学 Hypersonic aircraft Larger Dynamic Doppler quick capturing method and communication system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104407323A (en) * 2014-12-11 2015-03-11 中国工程物理研究院电子工程研究所 Measuring method for pseudo code delay of spread spectrum signal with high dynamic range and low signal-to-noise ratio
CN109495410A (en) * 2018-09-28 2019-03-19 西南电子技术研究所（中国电子科技集团公司第十研究所） High dynamic PCM/FM signal(-) carrier frequency precise Estimation Method
CN110518936A (en) * 2019-07-22 2019-11-29 西安电子科技大学 Hypersonic aircraft Larger Dynamic Doppler quick capturing method and communication system

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
WANG YUANKAI;XU JIANZHONG: "A Study on High Accuracy Range Measurement Algorithm for MMW Radar Level Meter", JOURNAL OF TEST AND MEASUREMENT TECHNOLOGY, vol. 29, no. 6 *
冯婕, 肖骏雄, 韩纪龙等: "基于幅度比值的低复杂度频偏估计算法", 光学学报, vol. 35, no. 5, pages 112 - 117 *
段瑞枫, 刘荣科, 周游等: "一种低复杂度的极低信噪比高动态信号载波粗捕获算法", 航空学报, vol. 34, no. 3, pages 662 - 669 *
黄长文: "深空通信信号的捕获与检测技术研究", 《中国优秀硕士学位论文全文数据库·信息科技辑》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114244384A (en) * 2021-12-20 2022-03-25 浙江嘉科电子有限公司 Continuous wave peak value capturing circuit and method for zero intermediate frequency receiver
CN114244384B (en) * 2021-12-20 2023-06-16 浙江嘉科电子有限公司 Continuous wave peak value capturing circuit and method for zero intermediate frequency receiver

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