Anti-interference method based on time-frequency domain data fusion

Abstract

The invention discloses an anti-interference method based on time-frequency domain data fusion. The method comprises the following steps: sampling a received signal; the obtained sampling signal is divided into two branches to be processed, the frequency domain branch rf (n) carries out frequency domain anti-interference processing, and the time domain branch rt (n) carries out time domain anti-interference processing; performing time domain interference detection processing and time domain interference suppression processing on the time domain branch signal rt (n); performing frequency domain interference detection processing and frequency domain interference suppression processing on the frequency domain branch signal rf (n); and performing data fusion by using the weight obtained by the detection processing and the time domain and frequency domain anti-interference results obtained by the interference suppression processing to obtain a weighted overall anti-interference result. According to the invention, under the condition of effectively resisting strong interference of different signal domains, the integrity of signals and good demodulation performance can still be ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of data fusion and anti-interference, and relates to an anti-interference method based on time-frequency domain data fusion, which is suitable for anti-interference processing of a receiver under the existence of partial time and frequency domain interference. Background Art

[0002] The requirements for anti-interference capabilities of modern communications are increasing. The system needs to ensure absolute reliability under strong interference, which puts higher requirements on the system's ability to resist strong interference in multiple domains in complex electromagnetic interference environments. In order to further improve the system's anti-interference capabilities, especially the ability to resist different types of interference in some time domains and frequency domains, it is necessary to identify and process the interference in the signal domain to eliminate the interference. Most traditional signal domain processing methods can only target a single dimension of the time domain or frequency domain. Some signal domain anti-interference measures that can simultaneously target time and frequency two-dimensional interference have weak anti-interference capabilities when time and frequency domain interference exist at the same time, which limits their use scenarios in complex electromagnetic environments. Summary of the invention

[0003] (I) Purpose of the invention

[0004] The purpose of the present invention is to propose an anti-interference method based on time-frequency domain data fusion to solve the problem that the traditional technology has insufficient anti-interference ability when there is partial time and frequency domain interference at the same time.

[0005] (II) Technical solution

[0006] In order to solve the above technical problems, the present invention provides an anti-interference method based on time-frequency domain data fusion, and its implementation process specifically includes the following steps:

[0007] Step 1: Sample the received signal. The sampled signal can be expressed by the following formula (1):

[0008]

[0009] Where A represents the signal amplitude, T s is the time domain sampling interval, n is the sampling time, and n=0,1,…,N-1. s(·) and s j (·) represent the useful signal and interference signal respectively, f d represents the carrier Doppler frequency, is the initial phase of the carrier.

[0010] Step 2: Process the sampled signal obtained in step 1 into two branches, where the frequency domain branch r f (n) Perform frequency domain anti-interference processing, time domain branch r t (n) Perform time domain anti-interference processing. The specific expression is as follows:

[0011] r f (n) = r t (n) = r(n) (2)

[0012] Step 3: The time domain branch signal r obtained in step 2 t (n) Perform time domain interference detection processing, specifically:

[0013] Step 3.1: t (n) modulus value, and according to the period N t The sampling points are averaged to obtain the average result. Multiply the average result by the high threshold coefficient k th The high threshold T for time domain interference detection can be obtained th As shown in formula (3):

[0014]

[0015] Step 3.2 Determine the N in the cycle t Whether the sampling points exceed the high threshold T of time domain interference detection th If any sampling point exceeds the upper threshold, it is determined that the time domain branch signal has interference, and the weight α of the signal is t Set to 1; if no sampling point exceeds the upper threshold, it is determined that there is no interference in the time domain branch signal, and the weight α of the signal is t Set to 1000;

[0016] Step 4: The time domain branch signal r obtained in step 2 t (n) Perform time domain interference suppression processing, specifically:

[0017] Step 4.1 Average the results obtained in step 3.1 Multiply by the lower threshold coefficient k tl , we can get the lower threshold T for time domain interference removal tl As shown in formula (4):

[0018]

[0019] Step 4.2 Determine the N in the cycle t Whether the sampling points exceed the lower threshold T of time domain interference removal tl , record the position where the interference deletion threshold is exceeded, and convert the time domain branch signal r t The amplitude of the same position of (n) is set to 0, and the time domain anti-interference result is obtained

[0020] Step 5: The frequency domain branch signal r obtained in step 2 f (n) Perform frequency domain interference detection processing, specifically:

[0021] Step 5.1: f (n) According to the cycle N f Perform FFT processing on the sampling points to obtain the frequency domain result R after FFT processing f (n);

[0022] Step 5.2: R f (n) Take the modulus value and perform averaging to obtain the average result Multiply the average result by the high threshold coefficient k fh The high threshold T of frequency domain interference detection can be obtained fh As shown in formula (5):

[0023]

[0024] Step 5.3 Determine N f Whether the FFT result exceeds the high threshold T of frequency domain interference detection fh If it exceeds the upper threshold, it is determined that the frequency domain branch signal has interference, and the weight α of the signal is f Set to 1; if none of them exceeds the upper threshold, it is determined that there is no interference in the frequency domain branch signal, and the weight α of the signal is f Set to 1000;

[0025] Step 6: The frequency domain branch signal r obtained in step 2 f (n) Perform frequency domain interference suppression processing, specifically:

[0026] Step 6.1 Average the results from step 5.2 Multiply by the lower threshold coefficient k fl , we can get the lower threshold T of frequency domain interference removal fl As shown in formula (6):

[0027]

[0028] Step 6.2 Determine N f Whether the FFT result exceeds the lower threshold T of frequency domain interference removal fl , record the position that exceeds the interference deletion threshold, and convert the frequency domain result R after FFT processing obtained in step 5.1 f The amplitude of the same position of (n) is set to 0, and the frequency domain interference removal result is obtained

[0029] Step 6.3 According to the cycle N f The sampling points are processed by IFFT to obtain the frequency domain anti-interference result after IFFT processing.

[0030] Step 7: Use the weight α calculated in steps 3 and 5 t and α f , the time domain and frequency domain anti-interference results obtained in step 4 and step 6 Perform data fusion to obtain the weighted overall anti-interference result r j (n) is expressed as formula (7):

[0031]

[0032] (III) Beneficial effects

[0033] The anti-interference method based on time-frequency domain data fusion provided by the above technical solution has the following beneficial effects:

[0034] In order to overcome the problem that traditional interference detection and elimination methods have poor anti-interference effect when partial time and frequency domain interference exist at the same time; the present invention utilizes high and low thresholds to perform interference detection and suppression in different signal domains, and performs weighted data fusion on the time and frequency domain anti-interference results. While effectively resisting strong interference in different signal domains, the signal integrity and good demodulation performance can still be guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a processing flow chart of "an anti-interference method based on time-frequency domain data fusion" of the present invention;

[0036] Figure 2 and Figure 3 They are respectively diagrams of the anti-interference effect of “an anti-interference method based on time-frequency domain data fusion” of the present invention when partial interference in the time and frequency domains exists simultaneously. DETAILED DESCRIPTION

[0037] In order to make the purpose, content and advantages of the present invention more clear, the specific implementation methods of the present invention are further described in detail below in conjunction with the drawings and examples.

[0038] In order to overcome the problem that the traditional interference detection and elimination methods have poor anti-interference effect when there are partial time and frequency domain interferences at the same time, the present invention proposes an anti-interference method based on time and frequency domain data fusion. By using high and low thresholds to detect and suppress interference in different signal domains, and performing weighted data fusion on the time and frequency domain anti-interference results, the signal integrity and good demodulation performance can still be guaranteed while effectively resisting strong interference in different signal domains.

[0039] Reference Figure 1 As shown, the anti-interference method of this embodiment is based on time-frequency domain data fusion, and its implementation process specifically includes the following steps:

[0040] Step 1: Sample the received signal. The sampled signal can be expressed by the following formula (1):

[0041]

[0042] Where A represents the signal amplitude, T s is the time domain sampling interval, n is the sampling time, and n=0,1,…,N-1. s(·) and s j (·) represent the useful signal and interference signal respectively, f d represents the carrier Doppler frequency, is the initial phase of the carrier.

[0043] Step 2: Process the sampled signal obtained in step 1 into two branches, where the frequency domain branch r f (n) Perform frequency domain anti-interference processing, time domain branch r t (n) Perform time domain anti-interference processing. The specific expression is as follows:

[0044] r f (n) = r t (n) = r(n) (2)

[0045] Step 3: The time domain branch signal r obtained in step 2 t (n) Perform time domain interference detection processing, specifically:

[0046] Step 3.1: t (n) modulus value, and according to the period N t The sampling points are averaged to obtain the average result. Multiply the average result by the high threshold coefficient k th The high threshold T for time domain interference detection can be obtained th As shown in formula (3):

[0047]

[0048] Step 3.2 Determine the N in the cycle t Whether the sampling points exceed the high threshold T of time domain interference detection th If any sampling point exceeds the upper threshold, it is determined that the time domain branch signal has interference, and the weight α of the signal is t Set to 1; if no sampling point exceeds the upper threshold, it is determined that there is no interference in the time domain branch signal, and the weight α of the signal is t Set to 1000;

[0049] Step 4: The time domain branch signal r obtained in step 2 t (n) Perform time domain interference suppression processing, specifically:

[0050] Step 4.1 Average the results obtained in step 3.1 Multiply by the lower threshold coefficient k tl , we can get the lower threshold T for time domain interference removal tl As shown in formula (4):

[0051]

[0052] Step 4.2 Determine the N in the cycle t Whether the sampling points exceed the lower threshold T of time domain interference removal tl , record the position where the interference deletion threshold is exceeded, and convert the time domain branch signal r t The amplitude of the same position of (n) is set to 0, and the time domain anti-interference result is obtained

[0053] Step 5: The frequency domain branch signal r obtained in step 2 f (n) Perform frequency domain interference detection processing, specifically:

[0054] Step 5.1: f (n) According to the cycle N f Perform FFT processing on the sampling points to obtain the frequency domain result R after FFT processing f (n);

[0055] Step 5.2: R f (n) Take the modulus value and perform averaging to obtain the average result Multiply the average result by the high threshold coefficient k fh The high threshold T of frequency domain interference detection can be obtained fh As shown in formula (5):

[0056]

[0057] Step 5.3 Determine N f Whether the FFT result exceeds the high threshold T of frequency domain interference detection fh If it exceeds the upper threshold, it is determined that the frequency domain branch signal has interference, and the weight α of the signal is f Set to 1; if none of them exceeds the upper threshold, it is determined that there is no interference in the frequency domain branch signal, and the weight α of the signal is f Set to 1000;

[0058] Step 6: The frequency domain branch signal r obtained in step 2 f (n) Perform frequency domain interference suppression processing, specifically:

[0059] Step 6.1 Average the results from step 5.2 Multiply by the lower threshold coefficient k fl , we can get the lower threshold T of frequency domain interference removalfl As shown in formula (6):

[0060]

[0061] Step 6.2 Determine N f Whether the FFT result exceeds the lower threshold T of frequency domain interference removal fl , record the position that exceeds the interference deletion threshold, and convert the frequency domain result R after FFT processing obtained in step 5.1 f The amplitude of the same position of (n) is set to 0, and the frequency domain interference removal result is obtained

[0062] Step 6.3 According to the cycle N f The sampling points are processed by IFFT to obtain the frequency domain anti-interference result after IFFT processing.

[0063] Step 7: Use the weight α calculated in steps 3 and 5 t and α f , the time domain and frequency domain anti-interference results obtained in step 4 and step 6 Perform data fusion to obtain the weighted overall anti-interference result r j (n) is expressed as formula (7):

[0064]

[0065] At this point, anti-interference based on time-frequency domain data fusion is completed from step one to step seven.

[0066] Figure 2 For the frequency domain anti-interference effect, Figure 3 This is the time domain anti-interference effect. Figure 2 and Figure 3 , the simulation input is the interference signal ratio of 20dB, and there are two types of interference signals: frequency domain comb interference with a frequency interval of 1MHz and an effective interference bandwidth of 200kHz, and time domain pulse interference with a repetition period of 1ms and a duty cycle of 20%. It can be seen from the figure that the positions where blocking interference exists in the time domain can be correctly detected, and after the interference suppression process, the amplitude of the position where interference exists is set to zero, and the positions where blocking interference exists in the frequency domain can be correctly detected, and after the interference suppression process, the amplitude of the position where interference exists is set to zero.

[0067] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An anti-interference method based on time-frequency domain data fusion, characterized in that: The following steps are involved: Step 1: sampling the received signal; Step 2: Process the sampled signal obtained in step 1 into two branches, where the frequency domain branch r f (n) Perform frequency domain anti-interference processing, time domain branch r t (n) performing time domain anti-interference processing; Step 3: The time domain branch signal r obtained in step 2 t (n) performing time domain interference detection processing; Step 4: The time domain branch signal r obtained in step 2 t (n) performing time domain interference suppression processing; Step 5: The frequency domain branch signal r obtained in step 2 f (n) performing frequency domain interference detection processing; Step 6: The frequency domain branch signal r obtained in step 2 f (n) performing frequency domain interference suppression processing; Step 7: Using the weights calculated in Steps 3 and 5, perform data fusion on the time domain and frequency domain anti-interference results obtained in Steps 4 and 6 to obtain a weighted overall anti-interference result.

2. The anti-interference method based on time-frequency domain data fusion according to claim 1, characterized in that: In step 1, the sampled signal is expressed by formula (1): Where A represents the signal amplitude, T s is the time domain sampling interval, n is the sampling time, and n=0,1,…,N-1. s(·) and s j (·) represent the useful signal and interference signal respectively, fd represents the carrier Doppler frequency, is the initial phase of the carrier.

3. The anti-interference method based on time-frequency domain data fusion according to claim 2, characterized in that: In step 2, the relationship between the branch signals is: r f (n)=r t (n)=r(n) (2)。 4. The anti-interference method based on time-frequency domain data fusion as claimed in claim 3, characterized in that: The process of step three is: Step 3.1: t (n) Take the modulus value and average the Nt sampling points to get the average result Multiply the average result by the high threshold coefficient k th , get the high threshold T for time domain interference detection th ; Step 3.2 Determine the N in the cycle t Whether the sampling points exceed the high threshold T of time domain interference detection th If any sampling point exceeds the upper threshold, it is determined that the time domain branch signal has interference, and the weight α of the signal is t Set to 1; If no sampling point exceeds the upper threshold, it is determined that there is no interference in the time domain branch signal, and the weight α of the signal is t Set to 1000.

5. The anti-interference method based on time-frequency domain data fusion according to claim 4, characterized in that: In step 3.1, the high threshold T for time domain interference detection th As shown in formula (3):

6. The anti-interference method based on time-frequency domain data fusion according to claim 5, characterized in that: The process of step four is: Step 4.1 Average the results obtained in step 3.1 Multiply by the lower threshold coefficient k tl , we can get the lower threshold T for time domain interference removal tl As shown in formula (4): Step 4.2 Determine the N in the cycle t The sampling point exceeds the lower threshold Ttl of the time domain interference deletion, records the position where the interference deletion threshold is exceeded, and converts the time domain branch signal r t The amplitude of the same position of (n) is set to 0, and the time domain anti-interference result is obtained 7. The anti-interference method based on time-frequency domain data fusion according to claim 6, characterized in that: The process of step five is: Step 5.1: f (n) Perform FFT processing on Nf sampling points to obtain the frequency domain result R after FFT processing f (n); Step 5.2: R f (n) Take the modulus value and perform averaging to obtain the average result Multiply the average result by the high threshold coefficient k fh , get the high threshold T of frequency domain interference detection fh ; Step 5.3 Determine N f Whether the FFT result exceeds the high threshold T of frequency domain interference detection fh If it exceeds the upper threshold, it is determined that the frequency domain branch signal has interference, and the weight α of the signal is f Set to 1; if none of them exceeds the upper threshold, it is determined that there is no interference in the frequency domain branch signal, and the weight α of the signal is f Set to 1000.

8. The anti-interference method based on time-frequency domain data fusion according to claim 7, characterized in that: In step 5.2, the high threshold T of frequency domain interference detection fh As shown in formula (5):

9. The anti-interference method based on time-frequency domain data fusion according to claim 8, characterized in that: The process of step six is: Step 6.1 Average the results from step 5.2 Multiply by the lower threshold coefficient k fl , we can get the lower threshold T of frequency domain interference removal fl As shown in formula (6): Step 6.2 Determine N f Whether the FFT result exceeds the lower threshold T of frequency domain interference removal fl , record the position that exceeds the interference deletion threshold, and convert the frequency domain result R after FFT processing obtained in step 5.1 f The amplitude of the same position of (n) is set to 0, and the frequency domain interference removal result is obtained Step 6.3 According to the cycle N f The sampling points are processed by IFFT to obtain the frequency domain anti-interference result after IFFT processing.

10. The anti-interference method based on time-frequency domain data fusion according to claim 9, characterized in that: In step 7, the weighted overall anti-interference result r j (n) is expressed as formula (7):

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