Long-time accumulation detection method for bistatic radar

Abstract

The invention relates to a long-time accumulation detection method based on a bistatic radar, and the method comprises the steps: firstly constructing a bistatic radar detection model, and receiving an echo signal generated by the reflection of an external radiation source signal through a target; pulse compression, distance dimension FFT, multiplication with a frequency response function generating a distance matched filter, conjugate multiplication with an exponential term causing distance migration, distance-Doppler dimension fast Fourier transform processing, Keystone linear frequency modulation Z transform processing and distance dimension IFFT processing are sequentially carried out on the echo signal, and a fifth echo signal is obtained; and carrying out peak detection on the fifth echo signal to detect the target and obtain the motion parameters of the target. Compared with the prior art, the method has the advantages of reducing energy accumulation loss caused by quantization errors when FFT processing is not interpolated in the distance dimension, effectively completing distance migration correction and pulse accumulation, reducing operation complexity caused by long-time accumulation and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of bistatic radars, and in particular to a long-term accumulation detection method for bistatic radars. Background Art

[0002] Modern defense and warfare are rapidly developing towards mobility, intelligence and autonomy. As a key part of the national defense and military equipment system, radar systems have been widely used in precision strikes, ground reconnaissance, air defense monitoring and other aspects thanks to their unique perception capabilities. With the continuous improvement of science and technology, the role of radar in the modern battlefield has become increasingly prominent. It not only enhances the accuracy of target detection and the accuracy of three-dimensional positioning, but also extends to imaging, recognition, communication and other fields. However, in the face of the rapid development of technologies such as drones, stealth fighters, absorbing materials and complex electromagnetic environments, the challenges faced by radar in information warfare are also increasing.

[0003] Target detection is one of the core functions of radar. For national security and defense, it is crucial to be able to detect potential threats in advance and issue early warnings. The difficulty of radar detecting moving targets lies in the complexity of spatial noise and clutter environment, as well as the low signal-to-noise ratio (SNR) of the echo. At present, the main types of radars include active radars and passive radars. In radar systems, there are single-base and multi-base. The transmitting and receiving equipment of single-base radars are located in the same position, which makes the radar system easy to be detected and attacked. In order to resist threats such as anti-radiation radar, bistatic radars significantly improve the safety of radar systems due to the separation of their transmitting and receiving equipment. In addition, bistatic radars can also illuminate aircraft or ground targets from multiple angles, which helps to enhance the energy of target echoes, making it more conducive to detecting moving targets. Due to the high maneuverability and small radar cross-section (RCS) of flying targets and ground moving targets, it is difficult to provide enough energy to detect targets by relying on a single or a small number of pulses. These targets are often obscured by complex noise and clutter backgrounds.

[0004] To solve this problem, existing technologies improve the echo signal-to-noise ratio by improving hardware performance, increasing the number of radars, adjusting radar layout, and increasing radar transmission power. However, these methods are limited by factors such as material technology, energy consumption, and construction costs, and are not widely used in domestic radar systems.

[0005] The invention patent with publication number CN101408616A discloses an inverse synthetic aperture radar imaging range alignment method suitable for low signal-to-noise ratio data, including: obtaining broadband echo data of a steadily flying target by an inverse synthetic aperture radar; after pulse compression of the echo data in the range direction, motion compensation is performed on the echo data with a rough estimate of the target radial velocity to eliminate Doppler blur, and the linear range movement of the target is corrected using the Keystone transform; the echo sequence is compensated with various Doppler values, and the peak value of the target range image after coherent accumulation is obtained at the corresponding Doppler, forming a synthetic range image with a higher signal-to-noise ratio. This method has a small amount of calculation, but cannot effectively correct the range migration problem caused by the target speed being too fast. Summary of the invention

[0006] The purpose of the present invention is to provide a long-term accumulation detection method for a bistatic radar in order to overcome the defects of the prior art.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] According to one aspect of the present invention, a long-term accumulation detection method based on a dual-base radar is provided. The method combines the range-dimensional FFT, the RFT-RD method and the KT-CZT method in a dual-radar detection model, and the steps include:

[0009] S1. Construct a dual-base radar detection model to receive the echo signal generated by the external radiation source signal reflected by the target;

[0010] S2, performing pulse compression on the echo signal to obtain a first echo signal;

[0011] S3, performing range-dimensional FFT on the first echo signal and multiplying the result by the frequency response function of the range-matched filter, and multiplying the result by the conjugate of the exponential term causing range migration to obtain a second echo signal;

[0012] S4, performing RFT-RD processing on the second echo signal to obtain a third echo signal;

[0013] S5. Perform KT-CZT processing on the third echo signal to obtain a fourth echo signal;

[0014] S6, performing distance-dimensional IFFT processing on the fourth echo signal to obtain a fifth echo signal;

[0015] S7. Perform peak detection on the fifth echo signal to detect the target and obtain the motion parameters of the target.

[0016] As a preferred technical solution, the bistatic radar detection model in S1 includes a bistatic radar receiver, an external radiation source, and a target to be detected.

[0017] As a preferred technical solution, the expression of the echo signal generated by the external radiation source signal received in S1 and reflected by the target is:

[0018]

[0019] Among them, S sur (t,τ) is the echo signal, P r is the echo signal power component; S(t) is the external radiation source signal; τ is the delay caused by the position and speed of the target; f d is the Doppler frequency shift; n0(t) is white noise.

[0020] As a preferred technical solution, the first echo signal expression in S2 is:

[0021]

[0022] Among them, S′ sur (t,τ) is the first echo signal, S * (t) is the conjugate of the external radiation source signal.

[0023] As a preferred technical solution, the second echo signal expression in S3 is:

[0024]

[0025] Among them, S(f,τ) is the frequency domain form of the reference channel signal; H k (f) is the frequency response function of the matched filter; P r is the echo signal power component; τ is the delay caused by the position and speed of the target; f d is the filter bandwidth.

[0026] As a preferred technical solution, the frequency response function H of the matched filter k (f) specifically:

[0027]

[0028] Among them, f d is the Doppler frequency shift; f d,k is the velocity value v k The corresponding Doppler frequency.

[0029] As a preferred technical solution, RFT-RD in S4 refers to random Fourier transform in the range-Doppler dimension.

[0030] As a preferred technical solution, the specific formula of RFT-RD is:

[0031]

[0032] Among them, G(r,f d ) is the third echo signal; M is the accumulated pulse number; r is the target distance search parameter; λ is the signal wavelength.

[0033] As a preferred technical solution, the KT-CZT processing in S5 is Keystone's linear frequency modulation Z transform processing.

[0034] As a preferred technical solution, KT-CZT treatment is specifically as follows:

[0035] The G(r,f d ) signal is multiplied by the Gaussian window function, and then FFT transformation is performed, and then multiplied by the Gaussian window function after FFT transformation, and then the signal output after an IFFT processing is performed, that is, the fourth echo signal. The formula of the fourth echo signal is:

[0036]

[0037] Among them, r∈[r min ,r max ] is the double base search range, v∈[v min ,v max ] is the dual-base speed search range, r0 and v0 are the initial dual-base distance and initial target speed respectively.

[0038] Compared with the prior art, the present invention has the following advantages:

[0039] 1. In a long-term accumulation detection method based on a dual-base radar, a dual-base radar detection model is constructed to receive an echo signal generated by an external radiation source signal reflected by a target; the echo signal is pulse compressed, FFT in the distance dimension, multiplied by the frequency response function that generates a distance matching filter, multiplied by the conjugate of the exponential term that causes distance migration, RFT-RD processing, KT-CZT processing, and IFFT processing in the distance dimension are performed to obtain a fifth echo signal, and the fifth echo signal is peak-detected to detect the target and obtain its motion parameters. The energy accumulation loss caused by the quantization error when performing FFT processing without interpolation in the distance dimension is reduced, and the distance migration correction and pulse accumulation can be effectively completed, thereby realizing the long-term accumulation detection of the dual-base radar.

[0040] 2. The long-term accumulation detection method based on dual-base radar in the present invention combines the distance dimension FFT, RFT-RD method and KT-CZT method in the dual radar detection model, so that the clutter accumulation speed is much smaller than the target, thereby having the effect of suppressing clutter on a macro scale. This method can also suppress clutter, making the radar system have higher reliability in detecting targets.

[0041] 3. The present invention starts from constructing a bistatic radar detection model, and the constructed bistatic radar detection model includes a bistatic radar receiver, an external radiation source, and a target to be detected. It can obtain an echo signal model that is more in line with the actual scene, so that the analysis can be specific and the analysis result is more accurate.

[0042] 4. In the present invention, the signal is pulse compressed to obtain the first echo signal, which can effectively improve the performance and signal-to-noise ratio of the radar system.

[0043] 5. The present invention performs RFT-RD transformation, i.e., fast Fourier transform of range-Doppler dimension, on the echo signal, which can effectively correct the range migration problem caused by the excessive speed of the target, thereby improving the detectability of the target;

[0044] 6. The present invention performs KT-CZT, i.e. Keystone linear frequency modulation Z transform processing on the echo signal, and converts the G(r,f d ) signal is multiplied with the Gaussian window function, FFT transformation is performed, and then it is multiplied with the Gaussian window function after FFT transformation, and then the output signal is processed once by IFFT. This method can greatly reduce the computational complexity of the method, thereby completing the energy accumulation of the echo signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of the steps of a long-term accumulation detection method based on a bistatic radar in the present invention;

[0046] Figure 2 A block diagram of a long-term accumulation detection method based on a bistatic radar in the present invention;

[0047] Figure 3 Schematic diagram of a bistatic radar target detection model in the present invention;

[0048] Figure 4 It is a spectrum diagram of a simulated signal in an embodiment;

[0049] Figure 5 This is a flow chart of RFT-RD processing in the present invention;

[0050] Figure 6 It is a KT-CZT processing flow chart in the present invention;

[0051] Figure 7 This is a distance migration diagram before the accumulation process in the embodiment;

[0052] Figure 8 It is a distance migration diagram after accumulation processing in the embodiment;

[0053] Fig. 9 This is a diagram before long-term accumulation treatment in the embodiment;

[0054] Fig.10 This is a diagram after long-term accumulation treatment in the embodiment. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0056] Example

[0057] In this embodiment, a long-term accumulation detection method based on a bistatic radar is applied. The steps of the method are as follows: Figure 1 As shown in FIG. 1 , it mainly includes: bistatic radar model construction, echo signal modeling and analysis, bistatic angle acquisition, pulse compression processing, range-Doppler random Fourier transform (Radon-Fourier Transform-Rang e-DopplerDomain, RFT-RD), Keystone linear frequency modulation Z transform processing (Keystone Transform-Chirp ZTransform, KT-CZT) processing. The method implementation block diagram is shown in FIG. Figure 2 As shown, the method steps are as follows:

[0058] S1. Construct a dual-base radar detection model to receive the echo signal generated by the external radiation source signal reflected by the target;

[0059] In this embodiment, the constructed dual-base radar detection model is as follows: Figure 3 As shown, R sur , R eef is a bistatic radar receiver, T x is an external radiation source, T ar is the target to be detected, R tt and R tr are the distances between the target and the external radiation source and the receiver, respectively; α is the pitch angle of the receiver after correction; θ is the target radial velocity correction angle; β is the bistatic angle to be determined; R ref Used to point to the external radiation source to receive the direct wave signal, R sur It is used to point to the target and receive the echo signal reflected by the target. The spectrum diagram of the echo signal generated by the established signal model is as follows: Figure 4 shown.

[0060] In this embodiment, by constructing a bistatic radar detection model, the external radiation source signal is continuously irradiated, and the echo signal data of the target is received and analyzed by the ground receiver. The echo signal model is as follows:

[0061]

[0062] Among them, S sur (t,τ) is the echo signal, P r is the echo signal power component; s(t) is the external radiation source signal; τ is the delay caused by the position and speed of the target; f d is the Doppler frequency shift; n0(t) is white noise.

[0063] In this embodiment, it is assumed that the target moves at a constant speed v, and the distances from the transmitting station and the receiving station at the initial moment are R tt and r tr ; and the distance between the transmitting station and the receiving station is fixed at L; α is the pitch angle of the receiver after correction, and θ is the target radial velocity correction angle; then the bistatic angle β can be calculated by the following formula:

[0064]

[0065]

[0066] Ignoring the first-order and higher components of the target distance, the Doppler shift is:

[0067]

[0068] Where, β is the bistatic angle; θ is the target radial velocity correction angle.

[0069] S2, performing pulse compression on the echo signal to obtain a first echo signal;

[0070] In this embodiment, the echo signal s sur (t,τ) for pulse compression

[0071]

[0072] Among them, r sur (t) is the distance between the moving target and the base; r is the target distance search parameter; c is the speed of light; τ is the time delay caused by the initial target position.

[0073] In this embodiment, the echo signal after pulse compression processing is expressed as follows:

[0074]

[0075] Among them, s′ sur (t,τ) is the echo signal after pulse compression, s* (t) is the conjugate of the external radiation source signal.

[0076] S3, performing a distance-dimensional Fast Fourier Transform (FFT) on the first echo signal, multiplying the signal with the frequency response function of the distance-matched filter, and multiplying the signal with the conjugate of the exponential term causing the distance migration, to obtain a second echo signal;

[0077] In this embodiment, different speed search values ​​(v1, v2, ..., v N ) constructs a Doppler filter, each velocity value v k Corresponding to a Doppler frequency f d,k .

[0078] In this embodiment, for each speed search value v k , construct a Doppler matched filter H k (f), its frequency response is:

[0079]

[0080] Among them, f d is the Doppler frequency shift; f d,k is the velocity value v k The corresponding Doppler frequency, Δf is the filter bandwidth.

[0081] In this embodiment, the echo signal after pulse compression is subjected to FFT and multiplied by the Doppler matched filter, and the echo signal can be written as follows:

[0082] S sur (f,τ)=FFT(s′ sur (t,τ))×H k (f);

[0083] In this embodiment, according to the above target distance search parameters, the formula can be written as:

[0084]

[0085] Among them, S(f,τ) represents the frequency domain form of the reference channel signal.

[0086] S4. Perform RFT-RD processing on the second echo signal. The processing process is as follows: Figure 5 As shown, a third echo signal is obtained;

[0087] In this embodiment, a random Fourier transform is performed as follows:

[0088]

[0089] Where G(r,fd ) is the signal S sur (f,τ) is the result after RFT processing; M is the number of accumulated pulses; r is the target distance search parameter; λ is the signal wavelength.

[0090] S5. Perform KT-CZT processing on the third echo signal. The processing process is as follows: Figure 6 As shown, a fourth echo signal is obtained;

[0091] In this embodiment, the signal G(r,f f ) performs Keystone's linear frequency modulation Z transform processing, which uses a Gaussian window function for transformation processing.

[0092] In this embodiment, the linear frequency modulation Z transform processing of Keystone is to convert the G(r,f d ) signal is multiplied with the Gaussian window function, then FFT is performed, and then multiplied with the window function after FFT transformation, and then an Inverse Fast Fourier Transform (IFFT) is performed, and finally the CZT processed signal is output. This method will greatly reduce the target search time and compensate for the loss of Doppler frequency in the matched filtering process.

[0093] In this embodiment, the target search time can be greatly reduced by using this method, and the loss of Doppler frequency in the matched filtering process can be compensated. The result after transformation is as follows:

[0094]

[0095] Among them, G CzT (r,f) is the result after CZT processing; r∈[r min ,r max ] is the double base search range, v∈[v min ,v max ] is the dual-base speed search range, r0 is the initial dual-base distance, and v0 is the initial target speed.

[0096] S6, performing distance-dimensional IFFT processing on the fourth echo signal to obtain a fifth echo signal;

[0097] S7. Perform peak detection on the fifth echo signal to detect the target and obtain its motion parameters.

[0098] In this embodiment, two sets of simulation signals generated from the same dual-base model are processed by the method and not processed by the method, and the results of the two are compared. Figure 7 , 8As shown in Figures 9 and 10, it can be clearly seen that this method reduces the energy accumulation loss caused by quantization error when performing FFT processing without interpolation in the distance dimension, effectively completes the range migration correction and pulse accumulation, and reduces the computational complexity caused by long-term accumulation.

[0099] In this embodiment, the simulation signal that has not been processed by this method will produce a range migration phenomenon when the target has a certain speed. Figure 7 As shown; and the distance migration between the distance dimension and the number of pulses after being processed by this method has been corrected, as shown Figure 8 shown.

[0100] In this embodiment, the simulated signal that has not been processed by this method cannot effectively distinguish the target from the clutter, and the target detection of the dual-base radar cannot be realized. The coherent accumulation result of the echo signal and the direct wave signal, such as Fig. 9 As shown; after the simulation signal processed by this method, after a long period of coherent accumulation, the result can clearly distinguish the target from the clutter, and correct the range migration problem caused by the moving target, such as Fig.10 shown.

[0101] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A long-term accumulation detection method based on a bistatic radar, characterized in that: The method combines the distance dimension FFT, RFT-RD method and KT-CZT method in the dual radar detection model, and the steps include: S1. Construct a dual-base radar detection model to receive the echo signal generated by the external radiation source signal reflected by the target; S2, performing pulse compression on the echo signal to obtain a first echo signal; S3, performing range-dimensional FFT on the first echo signal and multiplying the signal by the frequency response function of the range-matched filter, and then multiplying the signal by the conjugate of the exponential term causing range migration to obtain a second echo signal; S4, performing RFT-RD processing on the second echo signal to obtain a third echo signal; S5. Perform KT-CZT processing on the third echo signal to obtain a fourth echo signal; S6, performing distance-dimensional IFFT processing on the fourth echo signal to obtain a fifth echo signal; S7. Perform peak detection on the fifth echo signal to detect the target and obtain the motion parameters of the target.

2. The long-term accumulation detection method based on bistatic radar according to claim 1, characterized in that: The bistatic radar detection model in S1 includes a bistatic radar receiver, an external radiation source, and a target to be detected.

3. The long-term accumulation detection method based on bistatic radar according to claim 1, characterized in that: The expression of the echo signal generated by the external radiation source signal received in S1 and reflected by the target is: Among them, S sur (t,τ) is the echo signal, P r is the echo signal power component; S(t) is the external radiation source signal; τ is the delay caused by the position and speed of the target; f d is the Doppler frequency shift; n0(t) is white noise.

4. The long-term accumulation detection method based on bistatic radar according to claim 1, characterized in that: The expression of the first echo signal in S2 is: Among them, S′ sur (t,τ) is the first echo signal, S * (t) is the conjugate of the external radiation source signal.

5. The long-term accumulation detection method based on bistatic radar according to claim 1, characterized in that: The expression of the second echo signal in S3 is: Among them, S(f,τ) is the frequency domain form of the reference channel signal; H k (f) is the frequency response function of the matched filter; P r is the echo signal power component; τ is the delay caused by the position and speed of the target; f d is the Doppler shift.

6. The long-term accumulation detection method based on bistatic radar according to claim 5, characterized in that: The frequency response function of the matched filter H k (f) specifically: Among them, f d is the Doppler frequency shift; f d,k is the velocity value v k The corresponding Doppler frequency; Δf is the filter bandwidth.

7. The long-term accumulation detection method based on bistatic radar according to claim 1, characterized in that: The RFT-RD in S4 refers to the random Fourier transform in the range-Doppler dimension.

8. The long-term accumulation detection method based on bistatic radar according to claim 7, characterized in that: The specific formula of RFT-RD is: Among them, G(r,f d ) is the third echo signal; M is the accumulated pulse number; r is the target distance search parameter; λ is the signal wavelength.

9. The long-term accumulation detection method based on bistatic radar according to claim 1, characterized in that: The KT-CZT processing in S5 is Keystone's linear frequency modulation Z transform processing.

10. The long-term accumulation detection method based on bistatic radar according to claim 9, characterized in that: The KT-CZT treatment is specifically as follows: The G(r,f d ) signal is multiplied by the Gaussian window function, and then FFT transformation is performed, and then multiplied by the Gaussian window function after FFT transformation, and then the signal output after an IFFT processing is performed, that is, the fourth echo signal. The formula of the fourth echo signal is: Among them, r∈[r min ,r max ] is the double base search range, v∈[v min ,v max ] is the dual-base speed search range, r0 and v0 are the initial dual-base distance and initial target speed respectively.

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