CN114114184B - Cross interference suppression system and method between automobile radars - Google Patents
Cross interference suppression system and method between automobile radars Download PDFInfo
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- CN114114184B CN114114184B CN202111288684.6A CN202111288684A CN114114184B CN 114114184 B CN114114184 B CN 114114184B CN 202111288684 A CN202111288684 A CN 202111288684A CN 114114184 B CN114114184 B CN 114114184B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
Abstract
The invention discloses a cross interference suppression system and a method between automobile radars, which relate to the technical field of new generation information, wherein the system comprises a sparse constraint optimization unit and an interference signal separation unit, wherein the sparse constraint optimization unit is used for carrying out sparse constraint on radar target echo signals in a Fourier transform domain and carrying out sparse constraint on interference signals in a time domain so as to form a sparse optimization target function; the interference signal separation unit performs optimal separation on the target echo signal and the interference signal by using iterative soft threshold operation, so that the detectability rate of the radar target of the automobile radar under the strong interference condition is improved. A large number of actual measurement radar experiments show that the method can accurately detect the submerged target under the condition of strong interference, the signal to interference plus noise ratio of the target is improved from 5.06dB to 19.26dB, and the current latest automobile radar anti-interference method is broken through, so that the method has strong original competitiveness.
Description
Technical Field
The invention relates to a cross interference suppression system and a cross interference suppression method between automobile radars, and belongs to the technical field of new generation information.
Background
Because of the international telecommunication union recommendation standard, the working frequency range of the current automotive millimeter wave radar (hereinafter referred to as automotive radar) is 76-81 GHz. Although parameters of different transmitting waveforms, such as frequency adjustment, scanning period, bandwidth, starting frequency and the like, are adopted among the radars, the spectrums of signals transmitted by the radars overlap, and therefore interference among the radars is generated. Particularly, as the distribution density of high-level automatic driving vehicles on the same road section is increased, the cross interference between the radars becomes a technical bottleneck which seriously influences the performance of the radars. In recent years, scholars at home and abroad propose radar cross interference suppression based on traditional signal processing methods, such as adaptive noise cancellation methods, but the methods can only reduce interference intensity to a limited extent and cannot suppress strong interference. Therefore, how to suppress strong interference between radars is a technical bottleneck problem to be solved urgently.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a cross interference suppression system and a cross interference suppression method between automobile radars, so that the separation of target echoes and strong interference signals can be realized under the condition of strong interference between the radars.
In order to achieve the purpose, the invention adopts the technical scheme that: a cross interference suppression system between automobile radars comprises a sparse constraint optimization unit and an interference signal separation unit, wherein the sparse constraint optimization unit is used for carrying out sparse constraint on radar echo signals and carrying out sparse constraint on interference signals in a time domain so as to form a sparse optimization objective function; the interference signal separation unit is used for carrying out optimized separation on the target echo signal and the interference signal.
Furthermore, the sparse constraint optimization unit is used for performing sparse constraint on the radar echo signals in a fourier transform domain.
Further, the interference signal separation unit performs optimal separation on the target echo signal and the interference signal by using iterative soft threshold operation.
A cross interference suppression method between automobile radars comprises the following steps:
the method comprises the following steps: sending radar receiving signals to a sparse constraint optimization unit and an interference signal separation unit;
step two: sparse constraint optimization, namely performing sparse constraint on radar echo signals, and performing sparse constraint on interference signals in a time domain to form a sparse optimization objective function;
step three: and (4) separating interference signals, and performing optimized separation on the target echo signals and the interference signals by using iterative soft threshold operation.
Step four: and then compressing the distance, the speed and the direction of the processed signals to finally form target detection data.
Further, the step one specifically assumes that the target echo is s t The interference signal is s i If the system noise is n, the radar receiving signal y is,
y＝s i +s t +n (1)
suppose an echo signal s t The coefficient in the discrete Fourier transform A is x, then the above equation can be expressed as
y＝s i +Ax+n (2)
The theoretical derivation shows that x is a sparse signal, so that L1 norm can be utilized to respectively carry out sparse constraint on interference and echo signals, and a sparse optimization objective function can be obtained as
In the above formula, λ i And λ x Is a modelThe parameter of (1 | · | live through) 1 Is the L1 norm.
Further, the second step is specifically to establish a two-layer L1 optimization model for radar interference and echo signal separation according to formula (3) as
It is further deduced that the separation of the interference signal and the echo signal can be achieved by iterative soft threshold operations as
The soft threshold operation in the formula is defined as
soft(x，τ)＝x·max(1-τ/|x|，0). (6)
The final separated echo signals that can be obtained are:
the invention has the beneficial effects that: the method and the system device provided by the invention can effectively separate strong interference signals among the radars from radar receiving signals, accurately detect information such as the distance, the speed and the like of a vehicle target, improve the cross interference resistance of the automobile radars and enable a plurality of automobile radars to work in the same dense area in a coexisting way.
Drawings
FIG. 1 is a schematic flow chart of a cross interference suppression system and method between automotive radars according to an embodiment of the present invention;
FIG. 2 is a diagram of the operation of a cross interference suppression system in a radar signal processor in an embodiment of the present invention;
FIG. 3 is a diagram illustrating a separation result of a target echo and a strong interference signal in a strong interference environment according to an embodiment of the present invention;
FIG. 4 shows the target detection result without any interference suppression in the embodiment of the present invention;
FIG. 5 is a diagram illustrating a target detection result of a conventional adaptive noise cancellation method under a strong interference condition;
fig. 6 is a diagram illustrating a target detection result in a strong interference environment according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood, however, that the detailed description herein of specific embodiments is intended to illustrate the invention and not to limit the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and the terminology used herein in the description of the present invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the present invention.
As shown in fig. 1, a cross interference suppression system between automotive radars includes a sparse constraint optimization unit and an interference signal separation unit, the sparse constraint optimization unit is configured to perform sparse constraint on radar echo signals in a fourier transform domain, perform sparse constraint on interference signals in a time domain, and further form a sparse optimization objective function, and the interference signal separation unit performs optimal separation on target echo signals and interference signals by using iterative soft threshold operation, so as to improve the detectability of radar targets of automotive radars under strong interference conditions.
Specifically, assume that the target echo is s t The interference signal is s i If the system noise is n, the radar receiving signal y is,
y＝s i +s t +n (1)
suppose an echo signal s t The coefficient in the discrete Fourier transform A is x, then the above equation can be expressed as
y＝s i +Ax+n (2)
It is known from theoretical derivation that a few nonzero values exist after the echo coefficient x is normalized, so that x is a sparse signal. In addition, the interference signal has better sparsity in the time domain. Therefore, the L1 norm can be used for respectively carrying out sparse constraint on interference and echo signals, and further a sparse optimization objective function can be obtained as
In the above formula, λ i And λ x Is the parameter of the model, | ·| calving 1 Is the L1 norm.
The interference signal separation unit performs optimal separation on the echo and the interference signal by using iterative soft threshold operation. Specifically, according to formula (3), a two-layer L1 optimization model for radar interference and echo signal separation is established as
It is further deduced that the separation of the interference signal and the echo signal can be achieved by iterative soft threshold operations as
The soft threshold operation in the formula is defined as
soft(x，τ)＝x·max(1-τ/|x|，0). (6)
The separated echo signal can be obtained
Referring to fig. 2, radar receiving signals are sent to the sparse constraint optimization unit and the interference signal separation unit of the invention, so that the purpose of suppressing cross interference is achieved, and then compression of distance, speed and direction is performed to form target detection data.
In the embodiment, the starting frequency of the automobile main radar is 77GHz, the working bandwidth is 500MHz, and the scanning period is 30us. The radar generating interference is 12 meters away from the main radar, the initial frequency is 77.3GHz, the working bandwidth is 300MHz, and the scanning period is 15us. In the process of collecting the actual measurement data of the radar, an electric vehicle is 10 meters away from the main radar at a speed of 5 m/s.
As can be seen from fig. 3, by implementing the method of the present invention, the interference signal component in the radar receiving signal is successfully separated, and the radar target echo is also successfully recovered.
Fig. 4 shows the target detection result without any interference suppression, and the target signal-to-interference-plus-noise ratio is 5.06dB.
Fig. 5 shows the result of radar target detection in an interference environment by using the existing adaptive noise cancellation method. From the results, it can be seen that the conventional adaptive method fails under the condition of strong interference, and the vehicle target cannot be correctly detected.
By implementing the system and method of the present invention, a vehicle target at a speed of 5m/s 10 meters from the host radar is successfully detected, and the results are shown in FIG. 6. The method of the invention improves the ratio of the target signal to the interference plus noise from 5.06dB to 19.26dB, breaks through the current latest automobile radar anti-interference method, and has strong original competitiveness.
From the above description and the experimental results of radar actual measurement, it can be seen that the method and system provided by the invention can effectively separate the strong interference signals between the radars from the radar receiving signals, accurately detect the distance, speed and other information of the vehicle target, improve the anti-cross interference performance of the automobile radar, and enable a plurality of automobile radars to work in the same dense area in a coexistence manner.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents or improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (4)
1. A cross interference suppression system between automobile radars is characterized by comprising a sparse constraint optimization unit and an interference signal separation unit, wherein the sparse constraint optimization unit is used for carrying out sparse constraint on a target echo signal and carrying out sparse constraint on an interference signal in a time domain so as to form a sparse optimization target function; the interference signal separation unit is used for optimally separating a target echo signal and an interference signal;
suppose the target echo is s t The interference signal is s i If the system noise is n, the radar receiving signal y is,
y＝s i +s t +n (1)
suppose an echo signal s t The coefficient in the discrete Fourier transform A is x, then the above equation can be expressed as
y＝s i +Ax+n (2)
The theoretical derivation shows that x is a sparse signal, so that L1 norm can be utilized to respectively carry out sparse constraint on interference and echo signals, and a sparse optimization objective function can be obtained as
In the above formula i And λ x Is the parameter of the model, | ·| non-woven phosphor 1 Is L1 norm;
specifically, according to formula (3), a two-layer L1 optimization model for radar interference and echo signal separation is established as
It is further deduced that the separation of the interference signal from the echo signal can be achieved by iterative soft threshold operations
The soft threshold operation in the formula is defined as
soft(x,τ)＝x·max(1-τ/|x|,0). (6)
The final echo signals that can be separated are:
2. the system according to claim 1, wherein the sparse constraint optimization unit is configured to sparsely constrain the target echo signal in a fourier transform domain.
3. The system of claim 1, wherein the interference signal separation unit performs optimal separation of the target echo signal and the interference signal by using an iterative soft threshold operation.
4. A cross interference suppression method between automobile radars is characterized by comprising the following steps:
the method comprises the following steps: sending the radar receiving signal to a sparse constraint optimization unit;
step two: sparse constraint optimization, wherein sparse constraint is carried out on a target echo signal, and sparse constraint is carried out on an interference signal in a time domain, so that a sparse optimization objective function is formed;
step three: separating interference signals, and optimally separating target echo signals and the interference signals by using iterative soft threshold operation by an interference signal separation unit;
step four: compressing the processed signals in distance, speed and direction to finally form target detection data;
specifically, assume that the target echo is s t The interference signal is s i If the system noise is n, the radar receiving signal y is,
y＝s i +s t +n (1)
suppose an echo signal s t The coefficient in the discrete Fourier transform A is x, then the above equation can be expressed as
y＝s i +Ax+n (2)
The theoretical derivation shows that x is a sparse signal, so that L1 norm can be utilized to respectively carry out sparse constraint on interference and echo signals, and a sparse optimization objective function can be obtained as
In the above formula i And λ x Is the parameter of the model, | ·| calving 1 Is L1 norm;
specifically, according to the formula (3), a two-layer L1 optimization model for radar interference and echo signal separation is established as
Further development, separation of interference signals from echo signals can be achieved by iterative soft threshold operations
The soft threshold operation in the formula is defined as
soft(x，τ)＝x·max(1-τ/|x|，0). (6)
The final separated echo signals that can be obtained are:
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