CN116755044A - Method for canceling frequency domain sliding expansion of external radiation source radar - Google Patents
Method for canceling frequency domain sliding expansion of external radiation source radar Download PDFInfo
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Abstract
The invention discloses a method for canceling frequency domain sliding expansion of an external radiation source radar, and belongs to the field of digital signal processing. The implementation method of the invention comprises the following steps: overlapping and segmenting the monitoring signal and the reference signal, and performing fast Fourier transform; utilizing the strong correlation between the reference signal and the multipath clutter on the same frequency point to inhibit the static clutter on one frequency point in the bandwidth; transforming the frequency domain signal after static clutter suppression to a time domain, and removing the overlapped part to obtain a complete time domain signal after clutter suppression; and performing distance-Doppler two-dimensional matched filtering, detecting the interference of the moving clutter, and performing step-by-step suppression on the moving clutter with different Doppler frequency shifts to ensure that the order of the filter is always first order, thereby obviously reducing the operation amount of an algorithm and reducing the occupation amount of a memory. The invention utilizes the principle of the radar signal of the external radiation source, can effectively inhibit the interference of braking and static noise waves, is easier to realize the real-time processing of the signal, is not limited to the radiation source signal with a specific structure, and has universality.
Description
Technical Field
The invention relates to a method for canceling frequency domain sliding expansion of an external radiation source radar, belonging to the field of digital signal processing.
Background
External source radar is a radar system that utilizes non-cooperative illumination sources (e.g., digital television broadcast signals) for target detection and tracking. Because of the advantages of wide coverage, good concealment, low cost, environmental protection, no pollution and the like, the method has attracted extensive attention of researchers in the past decades. The monitoring channel signal received by the external radiation source radar not only contains target echoes, but also strong direct waves and multipath clutter. The target echo signal in the monitoring channel signal is often 60-100dB lower than the clutter signal, which causes the target echo to be submerged in the echo spectrum. Clutter suppression is therefore the most important problem faced by external source radars.
At present, the external radiation source radar clutter suppression method is mainly divided into a space domain clutter suppression method and a time domain clutter suppression method. The airspace clutter suppression has a good suppression effect on the sidelobe clutter by a method of suppressing the sidelobe and forming the null, but has no suppression capability on the clutter in the main lobe. The common time domain methods include Venus algorithm, recursive least square algorithm, normalized least mean square algorithm, expansion cancellation algorithm, batch expansion cancellation algorithm and sliding expansion cancellation algorithm. These methods are often faced with computationally intensive problems, especially for high sample rate signals, which are difficult to apply in real-time signal processing.
Aiming at the problems, clark uses fast Fourier transform in a block least mean square algorithm, and a frequency domain block self-adaptive filter is provided, so that the algorithm operation speed is greatly improved. Zhuo proposes a clutter suppression method based on a subband wiener filter, which reduces the dimension of the wiener filter in the subband, thereby reducing the computational complexity. In recent years, researchers have proposed carrier domain cancellation methods based on the waveform characteristics of orthogonal frequency division multiplexing signals. These methods have the advantages of small calculation amount and small occupied memory. However, the carrier domain algorithm relies on demodulation and modulation of the orthogonal frequency division multiplexed signal, and has some limitations.
Disclosure of Invention
The invention mainly aims to provide a method for canceling the sliding expansion of an external radiation source radar frequency domain, which utilizes the principle of the external radiation source radar and the digital signal processing technology to realize the effective suppression of dynamic and static clutter based on a sliding expansion cancellation algorithm. The invention has the advantages of less operation, small occupied memory, good universality and the like.
The aim of the invention is achieved by the following technical scheme.
The invention discloses a method for canceling frequency domain sliding expansion of an external radiation source radar, which comprises the steps of overlapping and segmenting a monitoring signal and a reference signal, and performing fast Fourier transform; utilizing the strong correlation between the reference signal and the multipath clutter on the same frequency point to inhibit the static clutter on one frequency point in the bandwidth; transforming the frequency domain signal after static clutter suppression to a time domain, and removing the overlapped part to obtain a complete time domain signal after clutter suppression; and performing distance-Doppler two-dimensional matched filtering, detecting the interference of the moving clutter, and performing step-by-step inhibition on the moving clutter with different Doppler frequency shifts. The invention can effectively inhibit the interference of braking and static noise waves, has the advantages of less operation amount and small occupied memory, is easier to realize the real-time processing of signals, is not limited to radiation source signals with specific structures, and has universality.
The invention discloses a method for canceling frequency domain sliding expansion of an external radiation source radar, which comprises the following steps:
and step one, carrying out quadrature demodulation and digital down-conversion processing on the monitoring signal and the reference signal to obtain a time domain monitoring signal s (n) and a time domain reference signal r (n).
The time domain reference signal is expressed as
r(n)＝d(n) (1)
Wherein d (n) is a direct wave. Since the intensity of the direct wave is much higher than the noise, the effect of the noise is ignored.
The time domain monitoring signal is expressed as
Wherein N is p Is the amount of static clutter; a is that p And n p The amplitude and the time delay of the p-th static clutter are respectively; n (N) c Is the number of moving clutter; a is that c 、n c 、f c The amplitude, the time delay and the Doppler frequency of the c-th moving clutter are respectively; n (N) t Is the target number; a is that t 、n t 、f t The amplitude, the time delay and the Doppler frequency of the t-th target are respectively; f (f) s Is the sampling rate; z (n) is the monitor channel noise.
And step two, performing overlapping segmentation processing on the monitoring signal s (n) and the reference signal r (n) obtained in the step one.
The segmented mth segment signal is expressed as:
where m=1, 2, M, N step For step length of each segment, N seg (N seg ≥2N del +N step ) For the length of each segment, N del For a target maximum delay, n=1, 2,.. seg When x is more than or equal to-1/2 and less than or equal to 1/2, rect (x) is 1, otherwise, 0.
Step three, the segmented monitoring signal s obtained in the step two is subjected to m (n) performing a fast fourier transform FFT (Fast Fourier Transform); for the segmented reference signal r obtained in the step two m (n) FFT is performed.
Step 3.1: for the segmented reference signal r m (n) FFT is carried out to obtain a corresponding frequency domain reference signal R m (ω k ) The expression of which is shown below,
R m (ω k )＝FFT[r m (n)]＝FFT[d m (n)]＝D m (ω k ) (4)
where m=1, 2, M, d m (n) is the m-th direct wave,is the data after the m-th direct wave FFT, omega k ＝2πkf s /N seg ，k＝1,2,...,N seg N representing the frequency domain seg Sampling points, and the interval between the frequency domain sampling points is deltaf=f s /N seg 。
Step 3.2: for the segmented monitoring signal s m (n) FFT is carried out to obtain a corresponding frequency domain monitoring signal S m (ω k ) The expression of which is shown below,
where m=1, 2, M, Z m (ω k ) The noise of the signal is monitored for the mth frequency domain.
FFT for the p-th stationary clutter is represented as follows,
the FFT on the c-th dynamic clutter is shown below,
where the spacing Δf between the frequency domain samples is greater than the Doppler frequency of the target or clutter, i.e., ω k ≈ω k ±2πf c . Therefore, the expression (7) is expressed as follows,
as above, the FFT for the t-th target echo is expressed as follows,
substituting formulas (6), (8) and (9) into (5),
and fourthly, utilizing the frequency domain monitoring signal and the frequency domain reference signal obtained in the third step to inhibit clutter on frequency points in the bandwidth, and setting zero for coefficients of noise frequency points to obtain a frequency domain signal after clutter inhibition.
And 4.1, extracting effective frequency points in the frequency domain signal.
Handle on signalThe frequency points within the bandwidth are referred to as effective frequency points, and the frequency points outside the signal bandwidth are referred to as noise frequency points. Let the number of effective frequency points of the signal be N b The index set corresponding to the effective frequency point is:
the expression of the reference signal at the kth frequency point is:
R k ＝D k (12)
in the formula, k is E I, D k ＝[D 1,k ,…D m,k ,…D M,k ] T An expression of the kth frequency point of the direct wave;
the expression of the monitoring signal at the kth frequency point is:
in the formula, k is E I, obtained, R k And X is k Y and Y k The correlation of (2) is very small; if f c ≠f t X is then k And Y is equal to k Hardly related; and noise Z k And R is R k 、X k Y and Y k Neither is relevant.
Step 4.2 dividing the reference and monitoring signals at the kth (k.epsilon.I) frequency point into B blocks each of length M B =m/B. On the basis, M is taken back and forth by each reference signal and monitoring signal S The/2 points act as sliding windows.
The monitor signal for block B (b=0, 1., B-1) is:
the reference signals for the B (b=0, 1., B-1) block are:
and 4.3, constructing a static clutter subspace matrix.
Step 4.4 filtering each monitoring signal, b-th monitoring signalProjection to and X b Orthogonal subspaces, resulting in a canceled signal +.>
Wherein b=0, 1, B-1,is X b Is a conjugate transpose of (a).
Step 4.5, after clutter on the effective frequency points are eliminated, the coefficient of the noise frequency points is set to zero, and a frequency domain signal after static clutter suppression is obtained
And fifthly, performing inverse fast Fourier transform IFFT (Inverse Fast Fourier Transform) by utilizing the frequency domain signal after static clutter suppression obtained in the step four, and removing the overlapped part to obtain a complete time domain signal after static clutter suppression.
And 5.1, performing IFFT on the frequency domain signal after static clutter suppression.
The frequency domain signal after static clutter suppression is:
IFFT was performed on the M (m=1, 2,) th segment signal, i.e., the M-th row vector in equation (19), expressed as:
and 5.2, removing the overlapped part and obtaining a complete time domain signal after static clutter suppression.
And step six, performing distance-Doppler two-dimensional matched filtering by using the time domain monitoring signal o (n) obtained in the step five and the time domain reference signal r (n) obtained in the step one to obtain a matched filtering result.
Step seven, detecting whether the dynamic clutter interference exists or not by using the matched filtering result obtained in the step six; if no moving clutter interference exists, cancellation is finished; if the mobile clutter interference exists, the mobile clutter Doppler information is saved, and the steps eight, nine and ten are executed.
And step eight, utilizing the static clutter subspace matrix obtained in the step four and the dynamic clutter Doppler information obtained in the step seven, and utilizing the strong correlation of the clutter with the same Doppler frequency shift on the same frequency point to establish a dynamic clutter subspace corresponding to the Doppler frequency shift.
The dynamic clutter subspace is:
wherein k (k.epsilon.I) is the kth frequency point, f q (q=1, 2,) Q is the doppler frequency of the moving clutter and Q is the number of different doppler frequencies.
Step nine, utilizing the frequency domain signal after static clutter suppression obtained in the step fourAnd the dynamic clutter subspace +.>For the dynamic clutter subspace one by one->Clutter cancellation processing is performed to make the filter order always be the first order.
Step 9.1 let q=1, apply the frequency domain signalProjection to and +.>Orthogonal subspaces, resulting in a canceled signal
Where b=0, 1,..b-1.
Step 9.2 if q=q, thenOtherwise, q=q+1, the frequency domain signal +.>Projection to and +.>Orthogonal subspace, obtaining new canceled signal +.>
If Q is not equal to Q in step 9.3, the process returns to step 9.2. Otherwise the first set of parameters is selected,
and step ten, performing IFFT by using the frequency domain signals after the dynamic clutter suppression obtained in the step nine, and removing the overlapped part to obtain complete time domain signals after the dynamic clutter suppression, thereby realizing effective suppression of the dynamic clutter and the static clutter.
The beneficial effects are that:
1. the invention discloses a method for canceling frequency domain sliding expansion of an external radiation source radar, which utilizes strong correlation between a reference signal and multipath clutter on the same frequency point and utilizes uncorrelation between moving clutter and a moving target echo signal on the same frequency point to effectively restrain the moving clutter and the static clutter.
2. The invention discloses an external radiation source radar frequency domain sliding expansion cancellation method, which utilizes the strong correlation of clutter with the same Doppler frequency shift on the same frequency point to establish a corresponding moving clutter subspace, and performs clutter cancellation processing on one moving clutter subspace, so that the order of a filter is always first order, the operation amount of an algorithm is obviously reduced, and the memory occupation amount is reduced.
3. The invention discloses an external radiation source radar frequency domain sliding expansion cancellation method, which utilizes an external radiation source radar signal processing technology to carry out FFT on signals after overlapping segmentation and inhibit clutter on frequency points one by one in a bandwidth.
Drawings
FIG. 1 is a flow chart of a static clutter suppression method in an embodiment of the invention, which is an external radiation source radar frequency domain sliding expansion cancellation method.
FIG. 2 is a flow chart of a method for suppressing dynamic clutter in an embodiment of the method for canceling the sliding expansion of an external radiation source radar frequency domain according to the present invention
Fig. 3 is a schematic diagram of signal overlapping segments in an embodiment of the method for cancellation of frequency domain sliding expansion of an external radiation source radar according to the present invention.
Fig. 4 is a schematic diagram of a frequency domain sliding expansion cancellation algorithm in an embodiment of the present invention, which is an external radiation source radar frequency domain sliding expansion cancellation method.
Fig. 5 is a graph showing the result of a distance-doppler two-dimensional matched filtering before clutter suppression in an embodiment of the present invention, an external radiation source radar frequency domain sliding spread cancellation method.
Fig. 6 is a range-doppler two-dimensional matched filtering result after static clutter suppression in an embodiment of the present invention, an external radiation source radar frequency domain sliding spread cancellation method.
Fig. 7 is a range-doppler two-dimensional matched filtering result after dynamic and static clutter suppression in the embodiment of the invention, which is an external radiation source radar frequency domain sliding expansion cancellation method.
Fig. 8 is a signal-to-noise ratio comparison chart of a doppler domain target 1 in an embodiment of the present invention, an external radiation source radar frequency domain sliding spread cancellation method.
Fig. 9 is a signal-to-noise ratio comparison graph of a doppler domain target 2 in an embodiment of the present invention, an external radiation source radar frequency domain sliding spread cancellation method.
Detailed Description
The following detailed description of the present invention is provided in conjunction with the accompanying drawings and specific examples, and it should be noted that the described embodiments are merely intended to facilitate an understanding of the present invention and are not intended to be limiting in any way.
In the embodiment of the invention, the signal is a digital television terrestrial broadcast DTTB (Digital Television Terrestrial Broadcasting) signal in a single carrier mode, the bandwidth is 7.56MHz, and the sampling rate of a receiving end is 9MHz.
As shown in fig. 1 and 2, the method for canceling the frequency domain sliding expansion of the external radiation source radar disclosed in the embodiment specifically includes the following implementation steps:
and step one, carrying out quadrature demodulation and digital down-conversion processing on the monitoring signal and the reference signal to obtain a time domain monitoring signal s (n) and a time domain reference signal r (n).
The time domain reference signal is represented as,
r(n)＝d(n) (1)
wherein d (n) is a direct wave. Since the intensity of the direct wave is much higher than the noise, the effect of the noise is ignored.
The time-domain monitoring signal is represented as,
wherein N is p Is the amount of static clutter; a is that p And n p The amplitude and the time delay of the p-th static clutter are respectively; n (N) c Is the number of moving clutter; a is that c 、n c 、f c The amplitude, the time delay and the Doppler frequency of the c-th moving clutter are respectively; n (N) t Is the target number; a is that t 、n t 、f t The amplitude, the time delay and the Doppler frequency of the t-th target are respectively; f (f) s Is the sampling rate; z (n) is the monitor channel noise.
And step two, performing overlapping segmentation processing on the monitoring signal s (n) and the reference signal r (n) obtained in the step one. The schematic segmentation is shown in fig. 3. The segmented m-th segment signal is denoted as,
where m=1, 2, M, N step For step length of each segment, N seg (N seg ≥2N del +N step ) For the length of each segment, N del For a target maximum delay, n=1, 2,.. seg When-1/2 is less than or equal to x is less than or equal to1/2, rect (x) is 1, otherwise 0. The signal segmentation parameters are shown in table 1,
TABLE 1 Signal segmentation parameters
Step three, the segmented monitoring signal s obtained in the step two is subjected to m (n) performing FFT; for the segmented reference signal r obtained in the step two m (n) FFT is performed.
Step 3.1: for the segmented reference signal r m (n) FFT is carried out to obtain a corresponding frequency domain reference signal R m (ω k ) The expression of which is shown below,
R m (ω k )＝FFT[r m (n)]＝FFT[d m (n)]＝D m (ω k ) (4)
where m=1, 2, M, d m (n) is the m-th direct wave,is the data after the m-th direct wave FFT, omega k ＝2πkf s /N seg ，k＝1,2,...,N seg N representing the frequency domain seg Sampling points, the interval between the frequency sampling points is delta f=f s /N seg 。
Step 3.2: for the segmented monitoring signal s m (n) FFT is carried out to obtain a corresponding frequency domain monitoring signal S m (ω k ) The expression of which is shown below,
where m=1, 2, M, Z m (ω k ) The noise of the signal is monitored for the mth frequency domain.
FFT for the p-th stationary clutter is represented as follows,
the FFT on the c-th dynamic clutter is shown below,
where the spacing Δf between the frequency domain samples is greater than the Doppler frequency of the target or clutter, i.e., ω k ≈ω k ±2πf c . Therefore, the expression (7) is expressed as follows,
as above, the FFT for the t-th target echo is expressed as follows,
substituting formulas (6), (8) and (9) into (5),
and fourthly, utilizing the frequency domain monitoring signal and the frequency domain reference signal obtained in the third step to inhibit clutter on frequency points in the bandwidth, and setting zero for coefficients of noise frequency points to obtain a frequency domain signal after clutter inhibition. The frequency domain sliding expansion cancellation algorithm is schematically shown in fig. 4, and the cancellation input parameters are shown in table 2.
Table 2 frequency domain sliding expansion cancellation input parameters
And 4.1, extracting effective frequency points in the frequency domain signal.
The frequency point within the signal bandwidth is called effective frequency point, and is the signal bandThe frequency points outside the width are called noise frequency points. Let the number of effective frequency points of the signal be N b The index set corresponding to the effective frequency point is:
the expression of the reference signal at the kth frequency point is:
R k ＝D k (12)
in the formula, k is E I, D k ＝[D 1,k ,…D m,k ,…D M,k ] T An expression of the kth frequency point of the direct wave;
the expression of the monitoring signal at the kth frequency point is:
in the formula, k is E I, obtained, R k And X is k Y and Y k The correlation of (2) is very small; if f c ≠f t X is then k And Y is equal to k Hardly related; and noise Z k And R is R k 、X k Y and Y k Neither is relevant.
Step 4.2 dividing the reference and monitoring signals at the kth (k.epsilon.I) frequency point into B blocks each of length M B =m/B. On the basis, M is taken back and forth by each reference signal and monitoring signal S The/2 points act as sliding windows.
The monitor signal for block B (b=0, 1., B-1) is:
the reference signals for the B (b=0, 1., B-1) block are:
and 4.3, constructing a static clutter subspace matrix.
Step 4.4 filtering each monitoring signal, b-th monitoring signalProjection to and X b Orthogonal subspaces, resulting in a canceled signal +.>
Wherein b=0, 1, B-1,is X b Is a conjugate transpose of (a).
Step 4.5, after clutter on the effective frequency points are eliminated, the coefficient of the noise frequency points is set to zero, and a frequency domain signal after static clutter suppression is obtained
And fifthly, performing IFFT on the frequency domain signal subjected to static clutter suppression obtained in the step four, and removing the overlapped part to obtain a complete time domain signal subjected to static clutter suppression.
And 5.1, performing IFFT on the frequency domain signal after static clutter suppression.
The frequency domain signal after static clutter suppression is:
IFFT was performed on the M (m=1, 2,) th segment signal, i.e., the M-th row vector in equation (19), expressed as:
and 5.2, removing the overlapped part and obtaining a complete time domain signal after static clutter suppression.
And step six, performing distance-Doppler two-dimensional matched filtering by using the time domain monitoring signal o (n) obtained in the step five and the time domain reference signal r (n) obtained in the step one to obtain a matched filtering result.
As shown in FIG. 5, the matched filtering result before clutter suppression shows that the zero frequency and multipath clutter near the zero frequency are most prominent, and the target is completely covered; the result of matched filtering after static clutter suppression using the frequency domain sliding spread cancellation algorithm is shown in fig. 6, where it is known that both targets can be found, most zero frequency and clutter near zero frequency have been cancelled, but stronger non-zero frequency clutter still exists near the targets.
Step seven, detecting whether the dynamic clutter interference exists or not by using the matched filtering result obtained in the step six; if no moving clutter interference exists, cancellation is finished; if the mobile clutter interference exists, the mobile clutter Doppler information is saved, and the steps eight, nine and ten are executed.
And step eight, utilizing the static clutter subspace matrix obtained in the step four and the dynamic clutter Doppler information obtained in the step seven, and utilizing the strong correlation of the clutter with the same Doppler frequency shift on the same frequency point to establish a dynamic clutter subspace corresponding to the Doppler frequency shift.
The dynamic clutter subspace is:
wherein k (k.epsilon.I) is the kth frequency point, f q (q=1, 2,) Q is the doppler frequency of the moving clutter, Q is the number of different doppler frequencies.
Step nine, utilizing the frequency domain signal after static clutter suppression obtained in the step fourAnd the dynamic clutter subspace +.>For the dynamic clutter subspace one by one->Clutter cancellation processing is performed to make the filter order always be the first order.
Step 9.1 let q=1, apply the frequency domain signalProjection to and +.>Orthogonal subspaces, resulting in a canceled signal
Where b=0, 1,..b-1.
Step 9.2 if q=q, thenOtherwise, q=q+1, the frequency domain signal +.>Projection to and +.>Orthogonal subspace, obtaining new canceled signal +.>
If Q is not equal to Q in step 9.3, the process returns to step 9.2. Otherwise the first set of parameters is selected,
and step ten, performing IFFT by using the frequency domain signal after the dynamic clutter suppression obtained in the step nine, and removing the overlapped part to obtain a complete time domain signal after the dynamic clutter suppression.
For the stronger moving clutter in fig. 6, a corresponding clutter subspace is established, the distance-Doppler two-dimensional matched filtering result after the moving clutter cancellation is shown in fig. 7, and the clutter near the target is effectively restrained from the figure. For further analysis of the performance of the cancellation algorithm, fig. 8 and 9 are graphs comparing the signal-to-noise ratios of target 1 and target 2, respectively, in the doppler domain. Meanwhile, table 3 gives the corresponding signal-to-noise ratios, respectively. Combining the graph and the table, the signal-to-noise ratio is improved by nearly 3dB after the dynamic clutter suppression. The method can obviously improve the signal-to-noise ratio of the target after inhibiting the dynamic noise.
TABLE 3 SNR after clutter suppression
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Claims (8)
1. A method for canceling frequency domain sliding expansion of an external radiation source radar is characterized in that: comprises the steps of,
performing quadrature demodulation and digital down-conversion processing on the monitoring signal and the reference signal to obtain a time domain monitoring signal s (n) and a time domain reference signal r (n);
step two, overlapping and sectioning the monitoring signal s (n) and the reference signal r (n) obtained in the step one;
step three, the segmented monitoring signal s obtained in the step two is subjected to m (n) performing a fast fourier transform FFT (Fast Fourier Transform); for the segmented reference signal r obtained in the step two m (n) performing FFT;
step four, utilizing the frequency domain monitoring signal and the frequency domain reference signal obtained in the step three to inhibit clutter on frequency points one by one in the bandwidth, and setting zero for coefficients of noise frequency points to obtain a frequency domain signal after clutter inhibition;
fifthly, performing inverse fast fourier transform IFFT (Inverse Fast Fourier Transform) on the frequency domain signal after static clutter suppression obtained in the fourth step, and removing the overlapped part to obtain a complete time domain signal after static clutter suppression;
step six, performing distance-Doppler two-dimensional matched filtering by using the time domain monitoring signal o (n) obtained in the step five and the time domain reference signal r (n) obtained in the step one to obtain a matched filtering result;
step seven, detecting whether the dynamic clutter interference exists or not by using the matched filtering result obtained in the step six; if no moving clutter interference exists, cancellation is finished; if the mobile clutter interference exists, the mobile clutter Doppler information is stored, and the steps eight, nine and ten are executed;
step eight, utilizing the static clutter subspace matrix obtained in the step four and the dynamic clutter Doppler information obtained in the step seven, and utilizing the strong correlation of the clutter with the same Doppler frequency shift on the same frequency point to establish a dynamic clutter subspace corresponding to the Doppler frequency shift;
step nine, utilizing the frequency domain signal after static clutter suppression obtained in the step fourAnd the dynamic clutter subspace +.>For the dynamic clutter subspace one by one->Clutter cancellation processing is carried out, so that the order of the filter is always the first order;
and step ten, performing IFFT by using the frequency domain signals after the dynamic clutter suppression obtained in the step nine, and removing the overlapped part to obtain complete time domain signals after the dynamic clutter suppression, thereby realizing effective suppression of the dynamic clutter and the static clutter.
2. The method for cancellation of frequency domain sliding spread of an external radiation source radar according to claim 1, wherein: in step one, the time domain reference signal is expressed as
r(n)＝d(n) (1)
Wherein d (n) is a direct wave; since the intensity of the direct wave is much higher than that of noise, the influence of noise is ignored;
the time domain monitoring signal is expressed as
Wherein N is p Is the amount of static clutter; a is that p And n p Respectively the sum time of the amplitudes of the p-th static clutterExtending; n (N) c Is the number of moving clutter; a is that c 、n c 、f c The amplitude, the time delay and the Doppler frequency of the c-th moving clutter are respectively; n (N) t Is the target number; a is that t 、n t 、f t The amplitude, the time delay and the Doppler frequency of the t-th target are respectively; f (f) s Is the sampling rate; z (n) is the monitor channel noise.
3. The method for cancellation of frequency domain sliding spread of an external radiation source radar according to claim 2, wherein: in the second step, the second step is to carry out the process,
the segmented mth segment signal is expressed as:
where m=1, 2, M, N step For step length of each segment, N seg (N seg ≥2N del +N step ) For the length of each segment, N del For a target maximum delay, n=1, 2, N seg When x is more than or equal to-1/2 and less than or equal to 1/2, rect (x) is 1, otherwise, 0.
4. A method of cancellation of frequency domain sliding spread of an external source radar as claimed in claim 3, wherein: the implementation method of the third step is that,
step 3.1: for the segmented reference signal r m (n) FFT is carried out to obtain a corresponding frequency domain reference signal R m (ω k ) The expression of which is shown below,
R m (ω k )＝FFT[r m (n)]＝FFT[d m (n)]＝D m (ω k ) (4)
where m=1, 2, M, d m (n) is the m-th direct wave,is the data after the m-th direct wave FFT, omega k ＝2πkf s /N seg ，k＝1,2,,N seg Representation frequencyN of domains seg Sampling points, and the interval between the frequency domain sampling points is deltaf=f s /N seg ；
Step 3.2: for the segmented monitoring signal s m (n) FFT is carried out to obtain a corresponding frequency domain monitoring signal S m (ω k ) The expression of which is shown below,
where m=1, 2, M, Z m (ω k ) Monitoring the noise of the signal for the m-th frequency domain;
FFT for the p-th stationary clutter is represented as follows,
the FFT on the c-th dynamic clutter is shown below,
where the spacing Δf between the frequency domain samples is greater than the Doppler frequency of the target or clutter, i.e., ω k ≈ω k ±2πf c The method comprises the steps of carrying out a first treatment on the surface of the Therefore, the expression (7) is expressed as follows,
as above, the FFT for the t-th target echo is expressed as follows,
substituting formulas (6), (8) and (9) into (5),
5. the method for cancellation of frequency domain sliding spread of an external source radar according to claim 4, wherein: the realization method of the fourth step is that,
step 4.1, extracting effective frequency points in the frequency domain signals;
the frequency points within the signal bandwidth are called effective frequency points, and the frequency points outside the signal bandwidth are called noise frequency points; let the number of effective frequency points of the signal be N b The index set corresponding to the effective frequency point is:
the expression of the reference signal at the kth frequency point is:
R k ＝D k (12)
in the formula, k is E I, D k ＝[D 1,k ,…D m,k ,vD M,k ] T An expression of the kth frequency point of the direct wave;
the expression of the monitoring signal at the kth frequency point is:
in the formula, k is E I, obtained, R k And X is k Y and Y k The correlation of (2) is very small; if f c ≠f t X is then k And Y is equal to k Hardly related; and noise Z k And R is R k 、X k Y and Y k None of which are related;
step 4.2 dividing the reference and monitoring signals at the kth (k.epsilon.I) frequency point into B blocks each of length M B =m/B; on the basis, M is taken back and forth by each reference signal and monitoring signal S 2 points as sliding windows;
the monitor signal for block B (b=0, 1., B-1) is:
the reference signals for the B (b=0, 1., B-1) block are:
step 4.3, constructing a static clutter subspace matrix;
step 4.4 filtering each monitoring signal, b-th monitoring signalProjection to and X b Orthogonal subspaces, resulting in a canceled signal +.>
Wherein b=0, 1, B-1,is X b Is a conjugate transpose of (2);
step 4.5, after clutter on the effective frequency points are eliminated, the coefficient of the noise frequency points is set to zero, and a frequency domain signal after static clutter suppression is obtained
6. The method for cancellation of frequency domain sliding spread of an external source radar of claim 5, wherein: the fifth implementation method is that,
step 5.1, performing IFFT on the frequency domain signal after static clutter suppression;
the frequency domain signal after static clutter suppression is:
IFFT was performed on the M (m=1, 2,) th segment signal, i.e., the M-th row vector in equation (19), expressed as:
step 5.2, removing the overlapped part and obtaining a complete time domain signal after static clutter suppression;
7. the method for cancellation of frequency domain sliding spread of an external source radar of claim 6, wherein: in the sixth step, the moving clutter subspace is:
wherein k (k.epsilon.I) is the kth frequency point, f q (q=1, 2, Q) is the doppler frequency of the moving clutter, Q is the number of different doppler frequencies.
8. The method for cancellation of frequency domain sliding spread of an external source radar according to claim 7, wherein: the implementation method of the step nine is that,
step 9.1 let q=1, apply the frequency domain signalProjection to and +.>Orthogonal subspaces, resulting in a canceled signal +.>
Wherein b=0, 1, B-1;
step 9.2 if q=q, thenOtherwise, q=q+1, the frequency domain signal +.>Projection to and +.>Orthogonal subspace, obtaining new canceled signal +.>
Step 9.3 if Q is not equal to Q, returning to step 9.2; otherwise the first set of parameters is selected,
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