CN114924121B - Frequency spectrum detection estimation method for extraterrestrial celestial body detector signal - Google Patents

Frequency spectrum detection estimation method for extraterrestrial celestial body detector signal Download PDF

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CN114924121B
CN114924121B CN202210787392.5A CN202210787392A CN114924121B CN 114924121 B CN114924121 B CN 114924121B CN 202210787392 A CN202210787392 A CN 202210787392A CN 114924121 B CN114924121 B CN 114924121B
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frequency
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sub
change rate
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CN114924121A (en
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陈少伍
李海涛
张娅楠
徐得珍
李赞
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CETC 54 Research Institute
63921 Troops of PLA
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63921 Troops of PLA
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    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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    • G01R23/16Spectrum analysis; Fourier analysis
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Abstract

The invention provides a frequency spectrum detection and estimation method for an extraterrestrial celestial body detector signal, which comprises the following steps of: estimating the frequency range and the frequency change rate range of a detector signal to be acquired by a ground station in advance; configuring signal acquisition parameters of a ground station; continuously dividing the frequency bandwidth of the signal acquisition unit into a plurality of sub-frequency bands at equal intervals, and continuously dividing the frequency change rate range into a plurality of frequency change rate estimation value sub-intervals at equal intervals; continuously dividing the frequency bandwidth of each sub-frequency band into a plurality of sub-frequency intervals at equal intervals; and the signal corresponding to the searched power peak value is the target signal. According to the invention, the terrestrial celestial body acquisition signals received by the ground antenna are divided into a plurality of sub-frequency bands, a plurality of sub-frequency intervals and a plurality of frequency change rate estimation value sub-intervals according to the frequency band range, so that rapid signal analysis processing is carried out, the calculation resources are reduced, and rapid signal analysis processing is realized.

Description

Frequency spectrum detection estimation method for extraterrestrial celestial body detector signal
Technical Field
The invention belongs to the technical field of spacecraft measurement and control, and particularly relates to a frequency spectrum detection and estimation method for signals of an extraterrestrial celestial body detector.
Background
The flying distance of the extraterrestrial celestial body detector is longer and longer, and the strength of a downlink signal of the extraterrestrial celestial body detector is weaker and weaker. At present, the farthest distance from a mars detector to the ground reaches 4 hundred million kilometers, the distance from planetary detectors such as a wooden star, a soil star and a king star to the ground is farther, the square of the distance from the detector to the ground is in direct proportion to the attenuation degree of signals, and therefore the strength of downlink signals of the detector is obviously weakened along with the increase of the distance. In addition, for the planetary detection task, the detector will go through the process of planetary capture, part of the detector will also realize landing on the planet, and the speed of the detector changes rapidly, thereby causing the dynamics of the downstream signal to be very large.
In a traditional mode, a ground station performs closed-loop signal estimation on a detector signal by adopting a phase-locked loop technology to complete detection on the detector signal. When the detector has relatively strong signal intensity and relatively small signal dynamic, closed-loop detection of the detector signal can be effectively finished. However, for the large dynamic and weak signals of the detector, the closed-loop signal estimation method cannot be well adapted, the detection and estimation difficulty of the detector signal is large, and the probability of signal lock losing is obviously increased.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a frequency spectrum detection and estimation method for the signal of the extraterrestrial celestial body detector, which can effectively solve the problems.
The technical scheme adopted by the invention is as follows:
the invention provides a frequency spectrum detection and estimation method for an extraterrestrial celestial body detector signal, which comprises the following steps of:
step 1, estimating a frequency range and a frequency change rate range of a detector signal to be acquired by a ground station in advance;
step 2, configuring signal acquisition parameters of the ground station according to the frequency range and the frequency change range of the detector signal to be acquired of the ground station estimated in advance in the step 1;
step 3, the ground station collects the detector signal by adopting the configured signal collection parameters to obtain an original collection signal;
step 4, dividing the original acquisition signal into a plurality of sections of acquisition signal units by taking the time length T as a period;
for each section of the acquired signal unit d T All execute step 5-step 8, search the signal collecting unit d T Target signal of (1):
step 5, collecting signal unit d T The frequency bandwidth of (a) is continuously divided into M sub-bands at equal intervals, and the acquisition signal of the M sub-band is represented as: d T (m),m=1,2,3,…,M;
Step 6, continuously dividing the frequency change rate range estimated in the step 1 into N frequency change rate estimation value subintervals at equal intervals;
acquisition signal d for m-th sub-band T (m) respectively calculating the frequency and frequency change rate two-dimensional compensation value of each frequency change rate estimation value subinterval, thereby obtaining N two-dimensional compensated acquisition signals g T (m, N), wherein N =1,2,3.., N;
step 7, continuously dividing the frequency bandwidth of the mth sub-band into Q sub-frequency intervals at equal intervals;
collecting signal g after two-dimensional compensation of the mth frequency sub-band in the nth frequency change rate estimation value sub-interval T (m, n), respectively calculating the Fourier transform result of each sub-frequency interval, thereby obtaining Q signals after Fourier transform, namely the three-dimensional acquisition signal G T (m,n,q);
Step 8, therefore, for the acquisition signal unit d T Performing fine search calculation on the M sub-frequency bands, the N frequency change rate estimation value sub-intervals and the Q sub-frequency intervals to obtain M, N and Q three-dimensional acquisition signals G T (m,n,q);
Comparing M N Q three-dimensional collected signals G T The power of (m, n, q), the sub-band sequence number corresponding to the power peak value, the frequency change rate estimation value sub-interval sequence number and the sub-frequency interval sequence number are the positions of the searched target signals, and then the target signals are searched;
and 9, estimating a frequency spectrum detection estimation value according to the searched target signal.
Preferably, in step 1, the frequency range of the detector signal is denoted as f min ,f max ]The frequency change rate range is represented by [ f' min ,f′ max ]:
Wherein:
f min the estimated value of the minimum frequency value of the detector signal to be acquired is obtained;
f max the estimated value of the maximum frequency value of the detector signal to be acquired;
f′ min for detection of the need to collectA minimum frequency rate estimate of the signal;
f′ max the estimated value of the maximum frequency change rate of the detector signal to be acquired is obtained;
in step 2, the configured signal acquisition parameters of the ground station comprise the frequency bandwidth B of the ground station 0 And a center frequency f B Obtained by the following formula:
B 0 =f max -f min
Figure BDA0003729247810000031
preferably, in step 5, a signal collecting unit d is adopted T Frequency bandwidth of (a) and frequency bandwidth B of the ground station arrangement 0 Are equal.
Preferably, in step 5, the collected signal d of each sub-band T (m) is represented by:
Figure BDA0003729247810000032
wherein: n is 0 Is noise, s (f (t)) is the target signal;
the meaning is as follows:
of the M subbands, only one subband has the target signal, assuming that there is the target signal in the z-th subband, where z is an unknown value; the other M-1 sub-bands are noise;
the step 6 specifically comprises the following steps:
the frequency change rate range [ f 'estimated in the step 1' min ,f′ max ]Equally spaced and continuously divided into N frequency rate of change estimate subintervals, expressed as: e (N), N =1,2,3.., N; therefore, the width Δ f' = E (N)/N of each frequency rate estimation value subinterval;
acquisition signal d for mth subband T (m) performing two-dimensional compensation of frequency and frequency change rate in the following manner to obtain two-dimensionally compensated acquisition signal g T (m,n):
Figure BDA0003729247810000041
Wherein:
j represents an imaginary unit;
f c (m) represents a lower boundary frequency compensation value of the mth sub-band;
f′ c (n) a lower boundary frequency change rate compensation value representing an nth frequency change rate estimate sub-interval;
wherein f is c (m) and f' c (n) is obtained using the formula:
f c (m)=(m-1)Δf+f min
f′ c (n)=(n-1)Δf′+f′ min
wherein: Δ f = B 0 and/M, representing the frequency bandwidth of each sub-band.
Preferably, step 7 specifically comprises:
collecting signal g after two-dimensional compensation of nth frequency change rate estimation value subinterval of mth subband T (m, n) is converted into a three-dimensional acquisition signal G by adopting the following formula T (m,n,q):
Figure BDA0003729247810000051
Wherein:
FFT represents fourier transform;
the meaning is as follows:
the frequency bandwidth Δ f of the mth sub-band is continuously divided into Q sub-frequency intervals at equal intervals, which is expressed as: FR (Q), Q =1,2,. -, Q; two-dimensionally compensated acquisition signal g for each sub-band T (m, n) performing Fourier transform in each sub-frequency interval to obtain Fourier transformed signal, namely three-dimensional acquisition signal G T (m,n,q)。
Preferably, in step 8, the signal G is acquired three-dimensionally T The power of (m, n, q) is denoted P T (m, n, q) byObtaining:
Figure BDA0003729247810000052
wherein:
Figure BDA0003729247810000053
meaning the result after the Fourier transform of the noise part;
P[N 0 ]represents N 0 Meaning: power after fourier transform of the noise part;
Figure BDA0003729247810000054
meaning the result of partial Fourier transform of the target signal s (f (t));
p [ S (m, n, q) ] represents the power of S (m, n, q), meaning: the target signal s (f (t)) is partially fourier transformed.
Preferably, in step 8, the power peak is represented by P T (m T ,n T ,q T );m T ,n T ,q T The meanings are respectively as follows: the subband number where the power peak is located, the frequency change rate estimation value subinterval number, and the subband interval number are expressed as:
(m T ,n T ,q T )=max[P T (m,n,q)]| m∈[1,M],n∈[1,N],q∈[1,Q]
the step 9 specifically comprises the following steps:
the frequency spectrum detection estimation value of the target signal comprises the following steps: accurate frequency estimation of a target signal
Figure BDA0003729247810000061
Accurate estimation value of frequency change rate
Figure BDA0003729247810000062
And accurate estimation value P/N of signal power noise spectral density ratio 0
Using the formulaSignal unit d T Accurate frequency estimation of intermediate target signal
Figure BDA0003729247810000063
And frequency rate of change accurate estimate
Figure BDA0003729247810000064
Figure BDA0003729247810000065
Figure BDA0003729247810000066
Obtaining a signal acquisition unit d by adopting the following formula T Accurate estimation value P/N of signal power noise spectral density ratio of intermediate target signal 0
P/N 0 =P T (m T ,n T ,q T )/P[N 0 ]
P[N 0 ]=N/(Δf/Q)
Obtain spectral curve G T (m T ,n T Q), wherein Q =1, 2., Q, includes an amplitude-frequency curve and a phase-frequency curve;
wherein:
spectral curve G T (m T ,n T Q) represents the abscissa FR (q) and the ordinate G T (m T ,n T Q) the resulting curve.
The frequency spectrum detection estimation method of the signal of the extraterrestrial celestial body detector provided by the invention has the following advantages:
according to the invention, the terrestrial celestial body acquisition signals received by the ground antenna are divided into a plurality of sub-frequency bands, a plurality of sub-frequency intervals and a plurality of frequency change rate estimation value sub-intervals according to the frequency band range, so that rapid signal analysis processing is carried out, the calculation resources are reduced, and rapid signal analysis processing is realized.
Drawings
FIG. 1 is a schematic flow chart of a method for estimating the spectrum detection of a signal of an extraterrestrial celestial object detector provided by the present invention;
FIG. 2 is a schematic diagram of a frequency and frequency rate of change two-dimensional compensation grid provided by the present invention;
fig. 3 is a diagram of a spectrum result of a signal of a mars detector provided by the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a frequency spectrum detection and estimation method for signals of an extraterrestrial celestial body detector, which comprises the steps of dividing a received acquisition signal frequency band into a plurality of sub-frequency bands, and dividing each sub-frequency band into a plurality of sub-frequency intervals; meanwhile, the estimated frequency change rate range is divided into a plurality of frequency change rate estimation value sub-intervals, so that rapid signal capture and tracking are carried out in three-dimensional spaces of the sub-frequency bands, the sub-frequency intervals and the frequency change rate estimation value sub-intervals, the frequency spectrum of the target signal is recovered, the estimation of the frequency, the frequency change rate and the signal power noise spectral density ratio of the target signal is completed, and the monitoring of the frequency spectrum of the weak signal of the extraterrestrial celestial body detector is realized. The invention can realize the capture and monitoring of extremely weak signals by utilizing a processing method of a plurality of sub-frequency bands, a plurality of sub-frequency intervals and frequency change rate estimation value sub-intervals, and is particularly suitable for monitoring and estimating the frequency spectrum of the extraterrestrial celestial body detector signal.
The invention provides a frequency spectrum detection and estimation method for a signal of an extraterrestrial celestial body detector, which comprises the following steps of:
step 1, estimating a frequency range and a frequency change rate range of a detector signal to be acquired by a ground station in advance;
in this step, the frequency range of the detector signal is denoted as f min ,f max ]The range of the frequency variation rate is represented by [ f' min ,f′ max ];
Wherein:
f min the estimated value of the minimum frequency value of the detector signal to be acquired is obtained;
f max the frequency maximum value estimation value of the detector signal to be acquired is obtained;
f′ min the minimum value of the frequency change rate of the detector signal to be acquired is estimated;
f′ max the frequency change rate maximum value estimation value of the detector signal to be acquired is obtained.
The position of the extraterrestrial celestial object cannot be accurately known, but initial estimation can be carried out according to prior information, so that the relative motion between the extraterrestrial celestial object (namely a detector) and the ground station can be initially determined, and the initial estimation of the frequency and the frequency change rate of the detector signal required to be acquired by the ground station is realized.
Step 2, configuring signal acquisition parameters of the ground station according to the frequency range and the frequency change range of the detector signal to be acquired of the ground station estimated in advance in the step 1;
in this step, the two configured signal acquisition parameters of the ground station are respectively the frequency bandwidth B of the ground station 0 And a center frequency f B Obtained by the following formula:
B 0 =f max -f min
Figure BDA0003729247810000081
step 3, the ground station collects the detector signal by adopting the configured signal collection parameters to obtain an original collection signal;
step 4, dividing the original collected signals into a plurality of sections of collected signal units by taking the time length T as a period;
for each section of the acquired signal unit d T All execute step 5-step 8, search and collect the signal unit d T Target signal of (1):
step 5, collecting signal unit d T Is continuously divided into M sub-bands at equal intervals, and the acquired signal of the M sub-band is expressed as:d T (M), M =1,2,3, \ 8230;, M; wherein, a signal collecting unit d T Frequency bandwidth of (a) and frequency bandwidth B of the ground station arrangement 0 Are equal.
Acquired signal d for each sub-band T (m) is represented by:
Figure BDA0003729247810000082
wherein: n is a radical of an alkyl radical 0 Is noise, s (f (t)) is a target signal;
the meaning is as follows:
of the M subbands, only one subband has the target signal, assuming that there is the target signal in the z-th subband, where z is an unknown value; the other M-1 sub-bands are noise.
Step 6, continuously dividing the frequency change rate range estimated in the step 1 into N frequency change rate estimation value subintervals at equal intervals;
specifically, the frequency change rate range [ f 'estimated in the step 1' min ,f′ max ]The equal-interval continuous division is carried out on N frequency change rate estimation value subintervals, and the frequency change rate estimation value subintervals are expressed as: e (N), N =1,2,3.., N; therefore, the width Δ f' = E (N)/N of each frequency change rate estimation value subinterval.
Acquisition signal d for m-th sub-band T (m) respectively calculating the frequency and frequency change rate two-dimensional compensation value of each frequency change rate estimation value subinterval, thereby obtaining N two-dimensional compensated acquisition signals g T (m, N), wherein N =1,2,3.., N;
as a specific implementation manner, the m-th sub-band collected signal d T (m) performing two-dimensional compensation of the frequency and the frequency change rate in the following manner to obtain a two-dimensionally compensated acquisition signal g T (m,n):
Figure BDA0003729247810000091
Wherein:
j represents an imaginary unit;
f c (m) represents a lower boundary frequency compensation value of the mth sub-band;
f′ c (n) a lower boundary frequency change rate compensation value representing an nth frequency change rate estimate sub-interval;
wherein f is c (m) and f' c (n) is obtained using the formula:
f c (m)=(m-1)Δf+f min
f′ c (n)=(n-1)Δf′+f′ min
wherein: Δ f = B 0 and/M, representing the frequency bandwidth of each sub-band.
As a specific implementation manner, the frequency and frequency change rate two-dimensional compensation grid shown in FIG. 2 can be manufactured, and each grid stores corresponding f in advance c (m) and f' c The value of (N) is, specifically, C (M, N) = (f) for the M-th point (M =1,2,3.. Multidot., M) on the horizontal axis and the N-th point (N =1,2,3.. Multidot., N) on the vertical axis, and the two-dimensional compensation matrix of the frequency and the frequency change rate is C (M, N) c (m),f c ′(n))。
For example, in the C (1, 3) grid of FIG. 2, f is stored c (1) And f' c (3) The value of (c). Thus, FIG. 2 can be looked up directly to quickly obtain the desired f c (m) and f' c The value of (n).
Step 7, continuously dividing the frequency bandwidth of the mth sub-band into Q sub-frequency intervals at equal intervals;
collecting signal g after two-dimensional compensation of nth frequency change rate estimation value subinterval of mth subband T (m, n), respectively calculating the Fourier transform result of each sub-frequency interval, thereby obtaining Q signals after Fourier transform, namely the three-dimensional acquisition signal G T (m,n,q);
In this step, the two-dimensionally compensated acquisition signal g of the mth sub-band in the nth frequency change rate estimation value sub-interval is acquired T (m, n) is converted into a three-dimensional acquisition signal G by adopting the following formula T (m,n,q):
Figure BDA0003729247810000101
Wherein:
FFT represents fourier transform;
the meaning is as follows:
the frequency bandwidth Δ f of the mth sub-band is continuously divided into Q sub-frequency intervals at equal intervals, which is expressed as: FR (Q), Q =1,2,. -, Q; two-dimensionally compensated acquisition signal g for each sub-band T (m, n) performing Fourier transform in each sub-frequency interval to obtain a Fourier transformed signal, namely a three-dimensional acquisition signal G T (m,n,q)。
Step 8, therefore, for the acquisition signal unit d T Performing fine search calculation on the M sub-frequency bands, the N frequency change rate estimation value sub-intervals and the Q sub-frequency intervals to obtain M, N and Q three-dimensional acquisition signals G T (m,n,q);
Comparing M N Q three-dimensional collected signals G T The power of (m, n, q), the sub-band sequence number corresponding to the power peak value, the frequency change rate estimation value sub-interval sequence number and the sub-frequency interval sequence number are the positions of the searched target signals, and then the target signals are searched;
in this step, a signal G is three-dimensionally acquired T The power of (m, n, q) is represented as P T (m, n, q) obtained by:
Figure BDA0003729247810000111
wherein:
Figure BDA0003729247810000112
meaning the result after the Fourier transform of the noise part;
P[N 0 ]represents N 0 The meaning of power of (a) is: power of the noise part after Fourier transform;
Figure BDA0003729247810000113
meaning the result of partial Fourier transform of the target signal s (f (t));
p [ S (m, n, q) ] represents the power of S (m, n, q), meaning: the target signal s (f (t)) is partially fourier transformed.
In this step, the peak power value is represented by P T (m T ,n T ,q T );m T ,n T ,q T The meanings are respectively as follows: the subband number where the power peak is located, the frequency change rate estimation value subinterval number, and the subband interval number are expressed as:
(m T ,n T ,q T )=max[P T (m,n,q)]| m∈[1,M],n∈[1,N],q∈[1,Q]
and 9, estimating a frequency spectrum detection estimation value according to the searched target signal.
In this step, the estimation value of the frequency spectrum detection of the target signal includes: accurate frequency estimation of target signal
Figure BDA0003729247810000121
Accurate estimation of frequency rate of change
Figure BDA0003729247810000122
And accurate estimation value P/N of signal power noise spectral density ratio 0
Obtaining a signal acquisition unit d by adopting the following formula T Accurate frequency estimation of intermediate target signal
Figure BDA0003729247810000123
And accurate estimate of frequency rate of change
Figure BDA0003729247810000124
Figure BDA0003729247810000125
Figure BDA0003729247810000126
Obtaining a signal acquisition unit d by adopting the following formula T Accurate estimation value P/N of signal power noise spectral density ratio of intermediate target signal 0
P/N 0 =P T (m T ,n T ,q T )/P[N 0 ]
P[N 0 ]=N/(Δf/Q)
Obtaining a spectral curve G T (m T ,n T Q), wherein Q =1, 2., Q, includes an amplitude-frequency curve and a phase-frequency curve;
wherein:
spectral curve G T (m T ,n T Q) represents the abscissa FR (q) and the ordinate G T (m T ,n T Q) the curve formed.
The computational complexity of the invention is analyzed as follows:
frequency bandwidth of B configured for ground station 0 The complexity of the computation may be expressed as O 1
O 1 ∝(2B 0 ) 2 ×M×N
After dividing into Q sub-frequency intervals, the computational complexity can be represented as O 2
O 2 ∝[(2B 0 /M) 2 ]×M×N=(2B 0 ) 2 ×N/M
It can be seen that O 2 =O 1 /M 2 The more the number of sub-bands (i.e., M) employed, the lower the computational complexity of the present invention and the effective reduction in time required.
Simulation analysis test
Conditions are as follows:
1. the extraterrestrial celestial object target analog signal is based on the following three practical conditions, and the nominal downlink frequency f is assumed 0 =8431MHz:
Operating condition one, frequency f 0 +20kHz, frequency change rate-100 Hz/s, signal power noise spectral density ratio P/N 0 =20dBHz。
Under the second working condition, the first working condition,frequency f 0 +20kHz, frequency change rate 100Hz/s, signal power noise spectral density ratio P/N 0 =20dBHz。
Operating mode three, frequency f 0 +20kHz, frequency change rate-10 Hz/s, signal power noise spectral density ratio P/N 0 =20dBHz。
2. And (3) data generation: the extraterrestrial celestial object target analog signal is converted into original data through acquisition, conversion and recording equipment (parameter configuration: acquisition and recording bandwidth is 2MHz, and quantization bit is 16 bit), and the original data is loaded in a file form.
3. The signal level, doppler and dynamic forecast file adds errors, frequency errors are +/-5 kHz, frequency change rate errors are +/-20 Hz/s, and signal power noise spectral density ratio errors are +/-5 dBHz on the basis of the 1.
4. The number of subchannels (i.e., Q) is 20 and the number of frequency and frequency variation rate compensation grids is 50, 10.
By adopting the method of the invention, the frequency change rate and the signal power noise spectral density ratio are estimated, and the result is as follows:
operating condition one, frequency f 0 +20.001kHz, frequency rate of change-99.017 Hz/s, P/N 0 =18.02dBHz。
Operating mode two, frequency f 0 +20.000kHz, frequency-doppler rate of change 98.68Hz/s, P/N 0 =18.10dBHz。
Operating mode three, frequency f 0 +19.999kHz, frequency-le rate of change-9.7 Hz/s, P/N 0 =17.73dBHz。
Therefore, the method can effectively monitor and estimate the signal spectrum of the extraterrestrial celestial body detector, and according to the results of the three working conditions, the frequency estimation precision reaches 1Hz, the frequency change rate estimation precision reaches 1Hz/s, and the signal power noise spectral density ratio estimation precision reaches 1.5dBHz.
And (3) analyzing the computational complexity:
conventional analytical method, O 1 ∝(2×2×10 6 ) 2 ×20×10=3.2×10 15 Process of the invention, O 2 =(2×2×10 6 /20) 2 ×20×10=8×10 12 It can be seen that the bookThe computational complexity of the invention is much less than that of the traditional method.
Analysis of practical application
Conditions are as follows:
1. mars lander signal theoretical value: frequency f 0 362.1kHz, frequency change rate 1Hz/s, signal power noise spectral density ratio P/N 0 =30dBHz。
2. And (3) data generation: the signals of the Mars lander are received by a ground antenna, are converted into original data through acquisition, conversion and recording equipment (parameter configuration: acquisition and recording bandwidth is 2MHz, and quantization bit number is 16 bit), and are loaded in a file form.
3. By adopting the method of the invention, the frequency change rate and the signal power noise spectral density ratio are estimated, and the result is as follows:
estimation result of Mars lander signal: frequency f 0 362.103kHz, frequency change rate of 0.95Hz/s, P/N 0 =31.29dBHz. The estimated spectrum of the Mars lander signal is shown in FIG. 3.
Therefore, by applying the method, the Mars lander signal frequency spectrum is successfully monitored and estimated, the deviation of the frequency of the signal from a theoretical value is 3Hz, the deviation of the frequency change rate from the theoretical value is 0.05Hz/s, and the deviation of the signal power noise spectral density ratio and a baseband test result is 1.29dBHz. The accuracy of the estimated values of the present invention is thus demonstrated to be very high.
The frequency spectrum detection estimation method of the signal of the extraterrestrial celestial body detector provided by the invention has the following advantages:
1. according to the invention, the terrestrial celestial body acquisition signals received by the ground antenna are divided into a plurality of sub-frequency bands, a plurality of sub-frequency intervals and a plurality of frequency change rate estimation value sub-intervals according to the frequency band range, so that rapid analysis processing of the signals is carried out, the calculation resources are reduced, and rapid analysis processing of the signals is realized.
2. The invention can realize high-precision estimation of signals, the estimation precision of target signal frequency reaches 1Hz, the estimation precision of frequency change rate reaches 1Hz/s, and the estimation precision of signal noise spectral density ratio reaches 1.5dBHz.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, many modifications and adaptations can be made without departing from the principle of the present invention, and such modifications and adaptations should also be considered to be within the scope of the present invention.

Claims (7)

1. A method for spectrum sensing estimation of a terrestrial celestial object detector signal, comprising the steps of:
step 1, estimating a frequency range and a frequency change rate range of a detector signal to be acquired by a ground station in advance;
step 2, configuring signal acquisition parameters of the ground station according to the frequency range and the frequency change range of the detector signal to be acquired of the ground station estimated in advance in the step 1;
step 3, the ground station collects the detector signal by adopting the configured signal collection parameters to obtain an original collection signal;
step 4, dividing the original collected signals into a plurality of sections of collected signal units by taking the time length T as a period;
for each section of the acquired signal unit d T All execute step 5-step 8, search and collect the signal unit d T Target signal of (2):
step 5, collecting signal unit d T The frequency bandwidth of (a) is continuously divided into M sub-bands at equal intervals, and the acquisition signal of the M sub-band is represented as: d T (m),m=1,2,3,…,M;
Step 6, continuously dividing the frequency change rate range estimated in the step 1 into N frequency change rate estimation value subintervals at equal intervals;
acquisition signal d for m-th sub-band T (m) respectively calculating the frequency and frequency change rate two-dimensional compensation value of each frequency change rate estimation value subinterval, thereby obtaining N two-dimensional compensated acquisition signals g T (m, N), wherein N =1,2,3.., N;
step 7, continuously dividing the frequency bandwidth of the mth sub-band into Q sub-frequency intervals at equal intervals;
estimating the rate of change of the mth frequency sub-band at the nth frequencyAcquisition signal g after two-dimensional compensation of evaluation subintervals T (m, n), respectively calculating the Fourier transform result of each sub-frequency interval, thereby obtaining Q signals after Fourier transform, namely the three-dimensional acquisition signal G T (m,n,q);
Step 8, therefore, for the acquisition signal unit d T Performing fine search calculation on the M sub-frequency bands, the N frequency change rate estimation value sub-intervals and the Q sub-frequency intervals to obtain M x N x Q three-dimensional acquisition signals G T (m,n,q);
Comparing M N Q three-dimensional collected signals G T The power of (m, n, q), the sub-band number corresponding to the power peak value, the sub-interval number of the frequency change rate estimation value and the sub-frequency interval number are the positions of the searched target signals, and then the target signals are searched;
and 9, estimating a frequency spectrum detection estimation value according to the searched target signal.
2. Method for spectral detection estimation of a extraterrestrial celestial detector signal according to claim 1, wherein in step 1, the frequency range of the detector signal is denoted as [ f [/f ] min ,f max ]The range of the frequency variation rate is represented by [ f' min ,f′ max ]:
Wherein:
f min the estimated value of the minimum frequency value of the detector signal to be acquired is obtained;
f max the estimated value of the maximum frequency value of the detector signal to be acquired;
f min the minimum value of the frequency change rate of the detector signal to be acquired is estimated;
f max the estimated value of the maximum frequency change rate of the detector signal to be acquired is obtained;
in step 2, the configured signal acquisition parameters of the ground station comprise the frequency bandwidth B of the ground station 0 And a center frequency f B Obtained by the following formula:
B 0 =f max -f min
Figure FDA0004055271480000021
3. method for spectral detection estimation of a extraterrestrial celestial object detector signal according to claim 2, wherein in step 5, a signal acquisition unit d is provided T Frequency bandwidth of (a) and frequency bandwidth B of the ground station arrangement 0 Are equal.
4. Method for the spectral detection estimation of a extraterrestrial celestial object detector signal as claimed in claim 3, characterized in that in step 5, the acquired signal d for each sub-band is T (m) is represented by:
Figure FDA0004055271480000031
wherein: n is 0 Is noise, s (f (t)) is the target signal;
the meaning is as follows:
of the M subbands, only one subband has the target signal, assuming that there is the target signal in the z-th subband, where z is an unknown value; the other M-1 sub-bands are noise;
the step 6 specifically comprises the following steps:
the frequency change rate range [ f ] estimated in the step 1 min ,f max ]Equally spaced and continuously divided into N frequency rate of change estimate subintervals, expressed as: e (N), N =1,2,3.., N; thus, the width Δ f' = E (N)/N of each frequency rate estimate subinterval;
acquisition signal d for m-th sub-band T (m) performing two-dimensional compensation of the frequency and the frequency change rate in the following manner to obtain a two-dimensionally compensated acquisition signal g T (m,n):
Figure FDA0004055271480000032
Wherein:
j represents an imaginary unit;
f c (m) represents a lower boundary frequency compensation value of the mth sub-band;
f c ' (n) represents a lower boundary frequency change rate compensation value for the nth frequency change rate estimate subinterval;
wherein f is c (m) and f c ' (n) is obtained using the formula:
f c (m)=(m-1)Δf+f min
f c ′(n)=(n-1)Δf′+f′ min
wherein: Δ f = B 0 and/M, representing the bandwidth of each sub-band.
5. The method for detecting and estimating the frequency spectrum of the extraterrestrial celestial object detector signal according to claim 4, wherein the step 7 is specifically:
collecting signal g after two-dimensional compensation of the mth frequency sub-band in the nth frequency change rate estimation value sub-interval T (m, n) is converted into a three-dimensional acquisition signal G by adopting the following formula T (m,n,q):
Figure FDA0004055271480000041
Wherein:
FFT represents fourier transform;
the meaning is as follows:
the frequency bandwidth Δ f of the mth sub-band is continuously divided into Q sub-frequency intervals at equal intervals, which is expressed as: FR (Q), Q =1,2,. -, Q; two-dimensionally compensated acquisition signal g for each sub-band T (m, n) performing Fourier transform in each sub-frequency interval to obtain Fourier transformed signal, namely three-dimensional acquisition signal G T (m,n,q)。
6. Spectral detection estimation of extraterrestrial celestial detector signals according to claim 5The method is characterized in that in step 8, three-dimensional acquisition signals G T The power of (m, n, q) is denoted P T (m, n, q) obtained by:
Figure FDA0004055271480000042
wherein:
Figure FDA0004055271480000043
meaning that the noise part is subjected to Fourier transform to obtain a result;
P[N 0 ]represents N 0 The meaning of power of (a) is: the power of the noise part after Fourier transform;
Figure FDA0004055271480000051
meaning that the target signal s (f (t)) is partially subjected to Fourier transform;
p [ S (m, n, q) ] represents the power of S (m, n, q), meaning: the target signal s (f (t)) is partially fourier-transformed.
7. Method for spectral detection estimation of a extraterrestrial celestial detector signal as claimed in claim 6, wherein in step 8, the power peak is denoted P T (m T ,n T ,q T );m T ,n T ,q T The meanings are respectively as follows: the subband number where the power peak is located, the frequency change rate estimation value subinterval number, and the subband interval number are expressed as:
(m T ,n T ,q T )=max[P T (m,n,q)]| m∈[1,M],n∈[1,N],q∈[1,Q]
the step 9 specifically comprises the following steps:
the frequency spectrum detection estimation value of the target signal comprises the following steps: accurate frequency estimation of target signal
Figure FDA0004055271480000052
Accurate estimation value of frequency change rate
Figure FDA0004055271480000053
And accurate estimation value P/N of signal power noise spectral density ratio 0
Obtaining a signal acquisition unit d by adopting the following formula T Accurate frequency estimation of intermediate target signal
Figure FDA0004055271480000054
And frequency rate of change accurate estimate
Figure FDA0004055271480000055
Figure FDA0004055271480000056
Figure FDA0004055271480000057
Obtaining a signal acquisition unit d by adopting the following formula T Accurate estimation value P/N of signal power noise spectral density ratio of intermediate target signal 0
P/N 0 =P T (m T ,n T ,q T )/P[N 0 ]
P[N 0 ]=N/(Δf/Q)
Obtaining a spectral curve G T (m T ,n T Q), wherein Q =1, 2.., Q, including amplitude-frequency curves and phase-frequency curves;
wherein:
spectral curve G T (m T ,n T Q) represents the abscissa FR (q) and the ordinate G T (m T ,n T Q) the resulting curve.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012078187A (en) * 2010-09-30 2012-04-19 Toshiba Corp Parameter detector, radar device, guidance system and parameter detection method
CN104852875A (en) * 2015-03-26 2015-08-19 中国人民解放军理工大学通信工程学院卫星通信军队重点实验室 Frequency offset estimation method for high-dynamic large-frequency-offset burst signals
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
CN111624402A (en) * 2020-05-31 2020-09-04 西南电子技术研究所(中国电子科技集团公司第十研究所) Method for accurately estimating carrier frequency of weak PM signal

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102005008734B4 (en) * 2005-01-14 2010-04-01 Rohde & Schwarz Gmbh & Co. Kg Method and system for detecting and / or eliminating sinusoidal noise in a noise signal

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012078187A (en) * 2010-09-30 2012-04-19 Toshiba Corp Parameter detector, radar device, guidance system and parameter detection method
CN104852875A (en) * 2015-03-26 2015-08-19 中国人民解放军理工大学通信工程学院卫星通信军队重点实验室 Frequency offset estimation method for high-dynamic large-frequency-offset burst signals
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
CN111624402A (en) * 2020-05-31 2020-09-04 西南电子技术研究所(中国电子科技集团公司第十研究所) Method for accurately estimating carrier frequency of weak PM signal

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于局部频谱连续细化的高精度频率估计算法;薛海中等;《西安电子科技大学学报》;20070225(第01期);全文 *

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