CN112904303A - Radar multi-target detection method combining clutter suppression and gridding FRFT processing - Google Patents
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Abstract
The invention relates to a radar multi-target detection method combining clutter suppression and gridding FRFT processing, and belongs to the technical field of radar signal processing and target detection. The method firstly solves the problem that the search range and the search step length of two independent variable parameters are difficult to quantify in the conventional FRFT domain target detection, and establishes a Doppler-acceleration two-dimensional search grid; then, aiming at each grid point in the Doppler-acceleration two-dimensional search grid, an adaptive matched filter technology is utilized to form an FRFT spectrum after clutter suppression, and the signal-to-noise-and-noise ratio is improved; and finally, the problem of multi-target detection is solved by utilizing a subspace projection technology. Compared with the conventional FRFT domain target detection method, the radar multi-target detection method based on FRFT processing has the advantages of clear parameter search grid, good signal-to-noise-ratio improvement performance, strong multi-target detection capability and suitability for engineering realization.
Description
Technical Field
The invention belongs to the technical field of radar signal processing and target detection, and particularly relates to a target detection technology in radar target detection.
Background
The wide-transmitting narrow-receiving radar (such as a Multiple-Input Multiple-Output (MIMO) radar) can obtain long-time observation of a target, and further can perform long-time coherent accumulation processing on target echo energy, improve the signal-to-noise-and-noise ratio, and improve the radar target detection performance. However, in the long-time coherent accumulation process, due to instability of the motion of the target itself, change of the radar observation angle and improvement of doppler resolution caused by long-time accumulation, the doppler of the target is easy to diffuse, and further target energy is not well accumulated. Fractional Fourier Transform (FRFT) processing can effectively solve this problem, especially for the case of doppler linear dispersion over time.
The target doppler changes linearly with time, i.e. the target makes uniform acceleration motion, and at this time, the target echo pulse train forms a Linear Frequency Modulation (LFM) signal. The FRFT process achieves the purpose of accumulating LFM signal energy by compensating for a phase difference between adjacent pulses due to such a linear time shift speed. However, in the field of radar target detection, the FRFT-based radar target detection method has not been well solved for three problems:
1) the search range and the search step size of two independent variable parameters in FRFT processing.
In literature, FRFT processing typically employs a set of parameters (p, u) to represent the argument parameters of its two dimensions, where p represents the transformation order, 0 < p ≦ 1, and u is analogous to the argument ω in the frequency domain. However, for radar target detection, two parameters, p and u, lack clear physical meanings, so there are large subjective factors (except for the search range of p) in determining the search range and the search step size of p and u, which results in lack of basis for determining the FRFT domain search grid, and at the same time, the FRFT domain search grid may be too thin and increase the amount of computation unnecessarily, and may also lose targets due to too thick.
2) Signal to noise ratio improvement in the FRFT domain.
In general, FRFT processing performs dot product (also called inner product) processing on an observed echo burst and an LFM steering vector formed by each (p, u) parameter set, thereby accumulating target energy and attempting to separate target and clutter in the FRFT domain for the purpose of improving signal-to-noise-and-noise ratio. This is done similarly to the MTD method in doppler domain processing. In practice, the target and the clutter may occupy partially the same (p, u) parameter unit, and the clutter energy is also accumulated while the target energy is accumulated, so the signal-to-noise ratio improvement is not optimal.
3) Multi-target detection in the FRFT domain.
A plurality of targets with different Doppler and acceleration possibly exist in the FRFT domain of one range-azimuth unit, and the phenomenon that the FRFT side lobe of a strong target covers the main lobe of a weak target easily occurs in consideration of the characteristics of the FRFT. The existing literature generally uses a Clean technology for processing, firstly, an echo of a strong target is estimated, then, the echo of the strong target is subtracted from a total echo, and then, a weak target is detected. However, this method is only suitable for the case where the strong target is very strong, otherwise the random initial phase of the strong target cannot be accurately estimated; meanwhile, higher requirements are also provided for the search step size of the two-dimensional parameters in the FRFT domain so as to ensure the estimation precision of the (p, u) parameter group.
In order to solve the three problems, the invention provides a radar multi-target detection method combining clutter suppression and gridding FRFT processing.
Disclosure of Invention
The invention aims to provide a radar multi-target detection method combining clutter suppression and gridding FRFT (fractional Fourier transform) processing aiming at the problem of long-time accumulation detection of a wide-transmitting narrow-receiving radar target, wherein the technical problems to be solved comprise:
(1) designing the search ranges and the search step lengths of two independent variable parameters in FRFT processing;
(2) signal-to-noise-and-noise ratio improvement in the FRFT domain;
(3) multi-target detection in the FRFT domain.
The radar multi-target detection method combining clutter suppression and gridding FRFT processing is characterized by comprising the following technical measures:
the method comprises the following steps: according to the expression form of the Doppler effect of the uniformly accelerated moving target in the radar echo pulse train, Doppler and acceleration are directly adopted as independent variable parameters of two dimensions of an FRFT domain, and then a search grid related to the two parameters is established on the basis of determining the search range and the search step length of the two parameters.
On one hand, Doppler and acceleration are inherent characteristics of a uniformly accelerated moving target and have definite physical meanings; on the other hand, in a radar coherent pulse train observation mode, the search range and the search step length of doppler and acceleration in FRFT processing can be theoretically determined, and the basic principle is as follows: the Doppler search range is determined by the pulse repetition frequency, and is generally between positive and negative half pulse repetition frequencies; the Doppler search step length is determined by the ratio of the pulse repetition frequency to the number of pulses; the acceleration is corresponding to the change of Doppler, the search range of the acceleration depends on the type of the target and the observation duration, the maximum and minimum speed and the bearable overload capacity of the target can be determined according to the type of the target, and then the search range of the acceleration of the target can be determined by combining the observation duration; the search step for the acceleration is then determined by the principle that, within the observation period, the change in acceleration within the search step cannot cause a change in doppler more than one doppler search step. The observation period in the above description refers to the product of the pulse repetition period and the number of pulses. In this way, the respective search ranges are divided into individual search grid points, referred to as doppler grid points and acceleration grid points, respectively, using the search step sizes of the two parameters doppler and acceleration, respectively, which in combination form a two-dimensional search grid for doppler and acceleration.
Step two: for each doppler-acceleration grid point, FRFT spectral values are calculated at the doppler-acceleration grid point using an adaptive matched filter technique.
The basic principle of the step is as follows: in the field of radar target adaptive detection, an adaptive matched filter estimates a background covariance matrix of a current detection range unit (called a detection unit) by using observation data of a plurality of range units (called reference units), then the purpose of suppressing clutter of the detection unit is achieved through the inversion operation of the background covariance matrix, and the purpose of accumulating echo energy on a given Doppler-acceleration grid point is achieved through coherent processing. Therefore, based on the search grid obtained in step one, for each doppler-acceleration grid point, the output of the adaptive matched filter is taken as the FRFT spectrum value on the doppler-acceleration grid point.
Step three: and searching the FRFT spectrum for the maximum spectrum value, and performing threshold judgment.
The basic principle is as follows: searching the FRFT spectrum for the maximum spectrum value, comparing the maximum spectrum value with a detection threshold, if the maximum spectrum value does not exceed the detection threshold, determining that the maximum spectrum value is not a target, and terminating the algorithm; if the detection threshold is exceeded, the target is considered, and the algorithm enters the step four. The detection threshold in the above description is calculated by combining a given false alarm probability on the basis of deriving a false alarm probability expression of the complex gaussian clutter adaptive matched filter under a non-target condition.
Step four: obtaining Doppler and acceleration parameters corresponding to the maximum spectral value searched in the third step, and constructing a projection operator; then, through projection operation, the LFM signal corresponding to the maximum spectrum value is removed from the observation data of the detection unit, and new observation data of the detection unit is formed; and repeating the second step to the fourth step to realize target-by-target detection.
Compared with the traditional radar target detection method based on FRFT processing, the radar multi-target detection method combining clutter suppression and gridding FRFT processing has the advantages that:
(1) the method solves the design problems of Doppler and acceleration search range and search step length in FRFT processing, so that the FRFT domain search grid cannot excessively increase calculated amount due to thinness, and cannot lose targets due to oversize.
(2) In the FRFT processing process, the output of the adaptive matched filter of each Doppler-acceleration grid point is used as the FRFT spectrum value, wherein the adaptive matched filter introduces background covariance matrix inversion operation, so clutter suppression is realized, and the signal-to-noise-and-noise ratio of the FRFT spectrum is effectively improved.
(3) The method utilizes projection operation to carry out target-by-target detection and elimination in the FRFT spectrum, and effectively solves the problem that FRFT side lobes of a large target cover a main lobe of a small target in the FRFT spectrum. The technology does not need to estimate the initial phase of a large target, and meanwhile, the estimation precision of Doppler and acceleration parameters is not high, so that the technology is convenient for engineering use.
Drawings
FIG. 1 is a flow chart of an implementation of a radar multi-target detection method combining clutter suppression and gridding FRFT processing.
Detailed Description
The invention is described in further detail below with reference to the drawings. Referring to the attached figure 1 of the specification, the specific implementation mode of the invention comprises the following steps:
(1) establishing a Doppler-acceleration two-dimensional search grid;
(2) preparing observation data of a detection unit and a reference unit, and estimating a background covariance matrix;
(3) aiming at each grid point in a Doppler-acceleration two-dimensional search grid, forming an FRFT spectrum after clutter suppression by using a self-adaptive matched filter technology;
(4) searching the FRFT spectrum for the maximum spectrum value, and performing threshold judgment; if the detection threshold is not exceeded, the target does not exist, and the algorithm is terminated; if the detection threshold is exceeded, the target is considered to exist, and the algorithm enters the step (5);
(5) under the condition that the target exists in the step (4), adopting projection operation to remove the LFM signal corresponding to the maximum spectral value from the observation data of the detection unit to form new observation data of the detection unit; and (4) replacing the original detection unit observation data in the step (3) with new detection unit observation data, and executing the step (3) again until the algorithm termination condition in the step (4) is met.
The above steps are described in detail below:
(1) and establishing a Doppler-acceleration two-dimensional search grid.
The radar emits coherent pulse train, the Doppler effect of the echo pulse train of the uniformly accelerated moving target is reflected in the radar echo pulse train after pulse compression and sampling
Wherein f isdtRepresenting the instantaneous doppler, corresponding to the instantaneous velocity of the target; f. ofdThe initial Doppler of the target in the current pulse train is shown, which is referred to as Doppler in the invention for short, and the initial speed of the corresponding target in the current pulse train is shown; a represents a target acceleration; λ represents a wavelength; t represents a pulse repetition period; l denotes a pulse number, L is 0, …, and L-1, where L denotes a burst length, that is, the number of pulses.
Doppler and acceleration are inherent features of target motion, with well-defined physical implications. The invention employs Doppler fdAnd two parameters of the acceleration a are used for constructing a two-dimensional parameter search space in FRFT processing, namely a Doppler-acceleration two-dimensional parameter space.
According to the radar signal theory, in the radar coherent pulse train observation mode, Doppler fdHas a value range of
Wherein
Represents the pulse repetition frequency; doppler fdStep size of search
The acceleration is corresponding to the change of the speed, the range of the acceleration depends on the type of the target and the observation duration, the maximum and minimum speeds and the bearable overload capacity of the target can be determined according to the type of the target, and then the target plus can be determined by combining the observation durationSearch range of speed, where observed duration refers to the product of pulse repetition period and number of pulses. Recording the maximum speed change of the target within the observation time length as | VmaxIf the acceleration is within a predetermined range, the acceleration is determined to be within a predetermined range
If the range is larger, the search range can be further reduced according to the maximum bearable overload capacity of the ship. The acceleration search step is determined based on the following principle: the change in acceleration within the search step cannot cause a change in doppler more than one doppler search step over the observation period, and thus,
thereby, the following doppler-acceleration two-dimensional search grid is formed:
doppler dimension: searching for a starting point
Search step size
Grid point
Grid number n, n is 0, …, L-1;
and (3) acceleration dimension: searching for a starting point
Search step size
Grid point
Grid serial number
Wherein,
indicating rounding up.
(2) The observation data of the detection unit and the reference unit are prepared, and a background covariance matrix is estimated.
The specific operation of this step is as follows:
preparing observation data
Since adaptive clutter suppression is to be performed, it is necessary to estimate the background covariance matrix of the currently detected range bin (referred to as the detection bin) using the observed data of neighboring range bins (referred to as reference bins). By x0The method comprises the steps of representing L multiplied by 1 dimensional observation data obtained by pulse pressure and sampling of L pulse echoes in a detection unit; by xkK is 1, …, and K represents L × 1-dimensional observation data in K reference units. For the target echo, the phase relationship between elements in the L × 1-dimensional observation data is as follows,
estimate the background covariance matrix
The background covariance matrix estimate of the detection cell is denoted as M, and the calculation formula is as follows,
wherein the superscript H denotes the conjugate transpose.
(3) And aiming at each grid point in the Doppler-acceleration two-dimensional search grid, forming an FRFT spectrum after clutter suppression by using the self-adaptive matched filter technology.
Searching for the (n, m) th grid point in the grid in two dimensions by using x0And M, calculating FRFT spectral values Γ (n, M) at the grid points as follows,
wherein s isn,mThe guide vector corresponding to the (n, m) th grid point is expressed by the calculation formula
Am＝diag([am,0…am,l…am,L-1]) Represents an acceleration compensation matrix, wherein
fd,n＝[fdn,0…fdn,l…fdn,L-1]TRepresents a Doppler vector, wherein
Superscript T denotes transpose; m-1Means that the inverse operation is performed on the background covariance matrix estimated value M, according to the radar signal processing theory, M-1Has the function of inhibiting clutter, particularly in M-1M contained in-1/2(i.e., M)-1Cholesky decomposition) of (c).
And traversing all grid points in the Doppler-acceleration two-dimensional search grid to form an FRFT spectrum after clutter suppression.
(4) Searching the FRFT spectrum for the maximum spectrum value, and performing threshold judgment; if the detection threshold is not exceeded, the target does not exist, and the algorithm is terminated; if the detection threshold is exceeded, the target is considered to be present, and the algorithm proceeds to step (5).
The specific operation of this step is as follows:
calculating the given false alarm probability P by using the following formulafaThe detection threshold η under the condition.
Wherein, bqIs the qth independent sample of the random variable b, Q is 1, …, Q is the total number of independent samples of the random variable b; the random variable b obeys a Beta distribution with parameters of (K-L +2, L-1); probability of false alarm PfaIs given by the radar system and generally takes the value 10-6。
② extracting the maximum spectral value in FRFT spectrum, marking as gammamax(n ', m '), n ' represents the number of Doppler dimensions corresponding to the maximum spectral value, and the grid points of the corresponding Doppler dimensions are expressed as
m' represents the serial number of the acceleration dimension corresponding to the maximum spectrum value, and the grid point of the corresponding acceleration dimension is recorded as
③ comparing gammamax(n ', m') and a detection threshold η, if ΓmaxIf (n ', m') < eta, judging that no target exists at the maximum spectrum value, and terminating the algorithm; if gamma ismaxAnd (n ', m') is larger than or equal to eta, judging that the target exists at the maximum spectral value, and entering the algorithm into the step (5).
(5) Under the condition that the target exists in the step (4), adopting projection operation to remove the LFM signal corresponding to the maximum spectral value from the observation data of the detection unit to form new observation data of the detection unit; and (4) replacing the original detection unit observation data in the step (3) with new detection unit observation data, and executing the step (3) again until the algorithm termination condition in the step (4) is met.
The method comprises the following specific steps:
utilizing Doppler dimension grid points obtained in the step (4)
And acceleration dimension grid points
Constructing a steering vector as follows
Calculating projection operator
Wherein I represents an L × L dimensional unit matrix.
Using projection arithmetic formula
I.e. data x can be observed from the detection unit0Middle rejection grid point
Corresponding LFM signal to obtain new observation data of detection unit, and recording the data
Fourthly, use
Replacement of x0And (5) executing the step (3) and the step (5) again until the algorithm termination condition of the third step in the step (4) is met.
Claims (5)
1. The radar multi-target detection method combining clutter suppression and gridding FRFT processing is characterized by comprising the following steps of:
s1, establishing a Doppler-acceleration two-dimensional search grid;
s2, preparing observation data of the detection unit and the reference unit, and estimating a background covariance matrix;
s3, aiming at each grid point in the Doppler-acceleration two-dimensional search grid, forming an FRFT spectrum after clutter suppression by using a self-adaptive matched filter technology;
s4, searching the FRFT spectrum for the maximum spectrum value, and performing threshold judgment; if the detection threshold is not exceeded, the target does not exist, and the algorithm is terminated; if the detection threshold is exceeded, the target is considered to exist, and the algorithm enters step S5;
s5, under the condition that the target exists in the step S4, the LFM signal corresponding to the maximum spectrum value is removed from the observation data of the detection unit by adopting projection operation to form new observation data of the detection unit; the original detecting unit observing data in step S3 is replaced with new detecting unit observing data, and step S3 is executed again until the algorithm terminating condition in step S4 is satisfied.
2. The radar multi-target detection method combining clutter suppression and gridding FRFT processing according to claim 1, wherein the step S1 specifically comprises:
s11, representation form in radar echo pulse train of uniform acceleration moving target according to Doppler effect
Selecting Doppler fdTwo parameters of acceleration a are used for constructing a two-dimensional parameter search space in FRFT processing, wherein fdtRepresenting instantaneous Doppler, fdThe method comprises the steps of representing target starting Doppler in a current pulse train, wherein Doppler is used for short in the invention, corresponding to the starting speed of a target in the current pulse train, a represents target acceleration, and lambda represents wavelength; t represents a pulse repetition period; l represents a pulse number, L is 0, …, L-1, L represents a burst length, i.e., the number of pulses;
s12 Doppler f according to targetdValue range of
And search step size
The grid points forming the doppler dimension are as follows: the starting point of the search is
The search step size is
Doppler dimensional grid points of
The doppler dimension grid number is n, n is 0, …, L-1,
is the pulse repetition frequency;
s13, forming a search grid point of an acceleration dimension;
and S14, combining the Doppler search grid point formed by the S12 and the acceleration search grid point formed by the S13 to form a Doppler-acceleration two-dimensional search grid.
3. The radar multi-target detection method combining clutter suppression and gridding FRFT processing according to claim 2, wherein the step S13 is specifically: firstly, according to the maximum speed variation | V that the target can reach in the observation time lengthmaxDetermining the variation range of the acceleration as
Then, the search step of the acceleration is determined as follows, according to the principle that the change of the acceleration in the search step cannot make the change of the Doppler more than one Doppler search step in the observation time length
The grid points forming the acceleration dimension are then as follows: the starting point of the search is
The search step size is
Acceleration dimension grid points are
Acceleration dimension grid serial number is
Wherein,
indicating rounding up.
4. The radar multi-target detection method combining clutter suppression and gridding FRFT processing according to claim 1, wherein the step S3 specifically comprises:
with respect to the (n, m) -th grid point in the doppler-acceleration two-dimensional search grid, the detection cell observation data x prepared in step S2 is used0And an estimated background covariance matrix M, calculating FRFT spectral values Γ (n, M) at the grid points as follows,
wherein s isn,mThe guide vector corresponding to the (n, m) th grid point is expressed by the calculation formula
Am＝diag([am,0 … am,l … am,L-1]) Represents an acceleration compensation matrix, wherein
fd,n＝[fdn,0 … fdn,l … fdn,L-1]TRepresents a Doppler vector, wherein
Superscript T denotes transpose; m-1Means to invert M;
and traversing all grid points in the Doppler-acceleration two-dimensional search grid to form an FRFT spectrum after clutter suppression.
5. The radar multi-target detection method combining clutter suppression and gridding FRFT processing according to claim 1, wherein the step S5 specifically comprises:
s51, using the Doppler dimension grid point corresponding to the maximum spectrum value obtained in step S4
And acceleration dimension grid points
Constructing a steering vector as follows
S52, according to the guide vector
Computing projection operators
Wherein I represents an L × L dimensional unit matrix.
S53, using projection arithmetic expression
Eliminates the observation data x of the detection unit0Middle grid point
Corresponding LFM signal to obtain new observation data of detection unit
S54, use
Replacement of x0Step S3 and step S5 are executed again until the algorithm termination condition in step S4 is satisfied.
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