A frequency-modulated continuous wave radar noise reduction ranging method based on weighted normalization

Abstract

The application discloses a frequency-modulated continuous wave radar noise reduction ranging method based on weighted normalization, mainly solves the problem of inaccurate frequency-modulated continuous wave radar ranging under frequency-modulated continuous wave interference and white noise background, and introduces a weighted normalization algorithm into a radar ranging framework, and proposes a radar noise reduction ranging method based on envelope weighted normalization.Under a traditional linear frequency-modulated continuous wave radar ranging model, a method of performing weighted normalization processing on a radar echo envelope interfered by noise is designed, compared with traditional linear frequency-modulated continuous wave radar ranging, the application can effectively reduce the influence of frequency-modulated continuous wave and white noise superimposed interference on the echo amplitude of the frequency-modulated continuous wave radar ranging signal, and effectively improves the ranging precision in combination with constant false alarm threshold detection.

Description

Technical Field

[0001] This invention belongs to the field of radar signal processing technology, specifically relating to a frequency-modulated continuous wave radar noise reduction and ranging method based on weighted normalization. Technical Background

[0002] Frequency-modulated continuous wave (FM-CW) radar is widely used due to its advantages such as simple structure, low cost, and ease of miniaturization. FM-CW radar can be further divided into linear and nonlinear types. Linear FM-CW radar has advantages such as high operating frequency, simultaneous transmission and reception, and low transmission power. FM-CW radar obtains the phase and frequency information of the target's intermediate frequency (IF) signal by transmitting continuously frequency-modulated (FM) continuous wave signals, thereby obtaining the target's range information. Due to its unique advantages, it has been widely used in both military and civilian fields. One of the most common applications in the civilian market is vehicle-mounted radar. However, this presents a problem: when a large number of linear FM signals are in the same space-time, interference between them can lead to inaccurate ranging in vehicle-mounted radar. Especially with the popularization of autonomous driving and intelligent driving technologies, the safety issues arising from this problem deserve attention and resolution. Current research on accurate ranging with frequency-modulated continuous wave (FM-CFW) radar mainly focuses on two aspects: optimizing intermediate frequency (IF) signal extraction and reducing environmental interference signals. It can be said that reducing interference from similar signals in the environment directly determines the radar's final ranging performance. Currently, the mainstream method for reducing interference and noise is through filter extraction; however, this method requires prior knowledge of the characteristics of the interference signals, making it complex and technologically demanding. Some inventors have also focused on extracting the IF signal from the echo signal to reduce noise interference, but this requires excessively high signal-to-noise ratios, making it unsuitable for practical applications and industrialization. Therefore, research on radar processing of IF signals and maximizing noise reduction in complex interference environments remains of significant academic and practical value. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and to propose a frequency-modulated continuous wave radar noise reduction and ranging method based on weighted normalization.

[0004] To achieve the above objectives, the present invention employs the following technical methods.

[0005] The frequency-modulated continuous wave radar noise reduction and ranging method based on weighted normalization includes the following steps:

[0006] Step 1: The echo signal after passing through the linear frequency modulation signal interference and white noise channel is received and sampled. The bandwidth of the echo signal is measured and discretized to obtain the echo signal m, whose length is K_m.

[0007] Step 2: For a signal m of length K_m, select L samples before and after time k, and window them so that each time k has two windows before and after it;

[0008] Step 3: Take the maximum value for the front and back windows of each frequency point to obtain the signal amplitude with the greatest influence factor on the amplitude at time k in the front and back windows, and select the smaller of the two maximum values ​​as the weighting factor;

[0009] Step 4: Take the reciprocal of the weight factor to obtain the weight at time k;

[0010] Step 5: Perform the same operation on the next time k+1 until the entire signal m is covered, and then the total weight W of each sample point of the signal m of length K_m is obtained;

[0011] Step 5: Finally, convert the amplitude m of each sample point in the original signal to... k Multiplying the result by the obtained weight at that point yields the normalized output signal. Complete the signal weighting and normalization operation.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0013] (1) The weighted normalized frequency modulated continuous wave radar noise reduction ranging method of the present invention can better improve the amplitude of the target signal in linear frequency modulation interference and white noise environment, and has better anti-noise performance compared with the traditional frequency modulated continuous wave radar ranging method.

[0014] (2) The weighted normalized frequency modulated continuous wave radar noise reduction ranging method of the present invention effectively improves the detection performance in complex environments and achieves higher ranging accuracy by using the weighted normalization method.

[0015] (3) The weighted normalized frequency modulated continuous wave radar noise reduction and ranging method of the present invention is simple to implement, has high computational efficiency, and can save a lot of time. Attached Figure Description

[0016] Figure 1 This is a flowchart of the steps in this method;

[0017] Figure 2 This is the overall implementation framework diagram;

[0018] Figure 3 The following is a diagram showing the ranging effect of the weighted normalized frequency-modulated continuous wave radar noise reduction ranging method:

[0019] Figure 4 This is a graph comparing the signal amplitude growth rate. Detailed Implementation

[0020] The present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. After reading this invention, any modifications of the invention in various equivalent forms by those skilled in the art will fall within the scope defined by the appended claims.

[0021] like Figure 1 As shown, the present invention provides a weighted normalized frequency-modulated continuous wave radar noise reduction and ranging method, comprising the following steps:

[0022] Step 1: Construct as follows Figure 2 The basic framework shown includes a linear frequency modulated (LFM) signal generation module, a transmission module, an LFM interference generation module, a signal receiving module, a constant false alarm rate (CFAR) processing module, a target, and a noise reduction and ranging module. The target distance is set to 40 meters and 76 meters.

[0023] Step 1: The echo signal after passing through the linear frequency modulation signal interference and white noise channel is received and sampled. The bandwidth of the echo signal is measured and discretized to obtain the echo signal m, whose length is K_m.

[0024] Step 2: For a signal m of length K_m, select L samples before and after time k, and window them so that each time k has two windows before and after it. The specific steps are as follows:

[0025] Step 2.1: Select the step size L;

[0026] Step 2.2: Select the sampling points with indices KL to K-1 before time k as the front window, and the sampling points with indices K+1 to K+L after time k as the back window;

[0027] Step 2.3: Obtain the signal sequence {[KL…K-1], K, [K+1…K+L]} of time k and its preceding and following windows.

[0028] Step 3: Take the maximum value for the windows before and after each frequency point to obtain the signal amplitude that has the greatest influence on the amplitude at time k in the windows before and after the frequency point. Select the smaller of the two maximum values ​​as the weighting factor. The specific steps are as follows:

[0029] Step 3.1: Calculate the maximum value of the window before time k: m_l_max_F = max[KL…K-1];

[0030] Step 3.2: Calculate the maximum value of the window after time k: m_l_max_B = max[K+1…K+L];

[0031] Step 3.3: Calculate the smaller value r between the maximum values ​​of the two windows before and after time k. k :r k=min[m_l_max_F,m_l_max_B].

[0032] Step 4: The frequency modulated continuous wave radar noise reduction and ranging method based on weighted normalization according to claim 1, characterized in that the weights in step S4 are calculated as follows: w k =1 / r k .

[0033] Step 5: Perform the same operation for the next time step k+1 until the entire signal m is covered. This yields the total weight W for each sample point of the signal m of length K_m. The specific process is as follows:

[0034] Step 5.1: Perform the same operation on the next time step k+1 until the entire signal m is covered, and the weight of each sample point of the signal m of length K_m is obtained;

[0035] Step 5.2: The total weight W of the entire signal is calculated as follows:

[0036] Step 6: Convert the amplitude m of each sample point in the original signal k Multiplying the result by the obtained weight at that point yields the normalized output signal. The calculation process is as follows:

[0037] like Figure 3 As shown, the target signal amplitude at 40 meters and 76 meters is significantly higher than the noise interference amplitude, proving that this method can effectively improve radar ranging accuracy.

[0038] like Figure 4 As shown, the amplitude is significantly increased by this method, proving that the invention is effective in increasing signal amplitude and achieving accurate ranging.

Claims

1. A frequency-modulated continuous wave radar noise reduction and ranging method based on weighted normalization, characterized in that, The structure includes the following steps: S1: The echo signal after passing through the linear frequency modulation signal interference and white noise channel is received and sampled. The bandwidth of the echo signal is measured and discretized to obtain the echo signal m, whose length is K_m. S2: For a signal m of length K_m, select L samples before and after time k, and window them so that each time k has two windows before and after it; S3: Take the maximum value for the front and back windows of each frequency point to obtain the signal amplitude with the largest influence factor on the amplitude at time k in the front and back windows, and select the smaller of the two maximum values ​​as the weighting factor. S4: Use the reciprocal of the weight factor to obtain the weight at time k; S5: Perform the same operation on the next time k+1 until the entire signal m is covered, and then the total weight W of each sample point of the signal m of length K_m is obtained; S6: Finally, the amplitude m of each sample point in the original signal is calculated. k Multiplying the result by the obtained weight at that point yields the normalized output signal. Complete the signal weighting and normalization operation.

2. The method for noise reduction and ranging of frequency-modulated continuous wave radar based on weighted normalization according to claim 1, characterized in that, The method for obtaining the windows before and after time k in step S2 is as follows: S21: Select step size L; S22: The sampling points with serial numbers from KL to K-1 before time k are taken as the front window, and the sampling points with serial numbers from K+1 to K+L after time k are taken as the back window; S23: Obtain the signal sequence {[KL…K-1], K, [K+1…K+L]} of time k and its preceding and following windows.

3. The method for noise reduction and ranging of frequency-modulated continuous wave radar based on weighted normalization as described in claim 1, characterized in that, The specific process of step S3 is as follows: S31: Calculate the maximum value of the window before time k: m_l_max_F = max[KL…K-1]; S32: Calculate the maximum value of the window after time k: m_l_max_B = max[K+1…K+L]; S33: Calculate the smaller value r between the maximum values ​​of the two windows before and after time k. k :r k =min[m_l_max_F, m_l_max_B].

4. The frequency modulated continuous wave radar noise reduction and ranging method based on weighted normalization according to claim 1, characterized in that, The weights in step S4 are calculated as follows: w k =1 / r k .

5. The method for noise reduction and ranging of frequency-modulated continuous wave radar based on weighted normalization as described in claim 1, characterized in that, The specific process of step S5 is as follows: S51: Perform the same operation on the next time k+1 until the entire signal m is covered, and then the weight of each sample point of the signal m with a length of K_m is obtained; S52: The total weight W of the entire signal is calculated as follows:

6. The method for noise reduction and ranging of frequency-modulated continuous wave radar based on weighted normalization according to claim 1, characterized in that, The specific process of step S6 is as follows: The amplitude m of each sample point in the original signal is... k Multiplying the result by the obtained weight at that point yields the normalized output signal.

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