A robust method for joint suppression of continuous wave interference and pulse interference

Abstract

The present invention discloses a robust continuous wave interference and pulse interference joint suppression method, comprising the following steps: S1: data processing the signal received by the M array element array antenna of the receiver to obtain an intermediate frequency sampling signal, that is, a snapshot signal received in MK*1 dimension, wherein K is the number of time domain taps; S2: using the MK*1 dimension snapshot signal obtained in step S1 and adopting a robust covariance matrix estimation method. The present invention uses a robust covariance matrix estimation algorithm to replace the conventional sample covariance estimation algorithm when using a space-time two-dimensional minimum power algorithm to suppress continuous wave interference, thereby eliminating the embodiment of pulse interference in the covariance matrix estimation result, and then, for the remaining pulse interference after continuous wave suppression, a robust interference suppression algorithm is used to suppress the pulse interference, thereby achieving the purpose of suppressing continuous wave interference and pulse interference at the same time without increasing the number of antenna array elements.

Description

Technical Field

[0001] The invention relates to the field of satellite navigation technology, and in particular to a robust continuous wave interference and pulse interference joint suppression method. Background Art

[0002] The Global Navigation Satellite System is a widely used positioning, navigation and timing system. With the advancement of science and technology, the scope of use of satellite navigation systems is gradually expanding, and the degree of reliance on them in various facilities is also increasing. However, the GNSS signal is about -130dBm when it reaches the ground, which is about 20dB lower than the noise. It is very susceptible to various intentional and unintentional interference. In addition, the continuous emergence of various electronic devices has also made the electromagnetic environment increasingly complex. In this case, weak GNSS signals face great threats. Even very simple interference equipment can interrupt the service of GNSS receivers in a wide area. Therefore, how to improve the anti-interference ability of GNSS receivers has always been a research hotspot.

[0003] Among the interferences to GNSS, the most common is high-power suppression interference. Suppression interference can be divided into narrowband interference and broadband interference. Narrowband interference refers to interference with a smaller ratio of bandwidth to signal bandwidth or a smaller absolute bandwidth. Interference with a ratio of interference bandwidth to signal bandwidth of less than 10% is usually called narrowband interference, and interference that does not meet the narrowband signal condition is called broadband interference. Broadband suppression interference is divided into continuous wave interference and pulse interference according to the continuity of the action time. Pulse interference can be divided into periodic pulse interference and non-periodic pulse interference, usually with a duty cycle of less than 20%. There are many sources of pulse interference. For example, radar, microwave, communication equipment, etc. will generate high-power pulse interference. There are also varying degrees of unconscious pulse interference around important facilities such as airports and radar sites.

[0004] In order to suppress suppression interference, the most commonly used algorithm is the space-time two-dimensional minimum power algorithm based on array antenna. Since it does not require calibration of the array antenna and does not require knowing the direction of the satellite signal, the algorithm is simple and effective, so it is widely used.

[0005] However, when the above most commonly used algorithms are actually used, the cost of array antennas will increase significantly as the number of array elements increases compared to single-antenna receivers. This often makes it impossible to receive signals in cost-sensitive civilian fields, such as unmanned driving. In addition, single-antenna receivers often cannot suppress broadband continuous wave interference. Taking a two-element array antenna receiver as an example, the conventional space-time minimum power algorithm can only suppress one broadband continuous wave interference. When there is one broadband continuous wave interference and one pulse interference, it is impossible to suppress both interferences at the same time without increasing the number of antenna elements. Summary of the invention

[0006] The purpose of the present invention is to provide a robust method for jointly suppressing continuous wave interference and pulse interference to solve the problem that when there is a broadband continuous wave interference and a pulse interference, the continuous wave interference and the pulse interference cannot be suppressed simultaneously without increasing the number of antenna array elements.

[0007] To achieve the above object, the present invention provides the following technical solution: comprising the following steps:

[0008] S1: Process the signal received by the M-element array antenna of the receiver to obtain an intermediate frequency sampling signal, that is, a snapshot signal received in MK*1 dimensions, where K is the number of time domain taps;

[0009] S2: using the MK*1-dimensional snapshot signal obtained in step S1 and adopting a robust covariance matrix estimation method, the robust covariance matrix is ​​estimated and the proportion of pulse interference in the signal is reduced to achieve the effect of improving the suppression of continuous wave interference;

[0010] S3: using the robust covariance matrix estimate obtained in step S2 to replace the covariance matrix estimate of the space-time two-dimensional minimum power algorithm, solving the optimal weights, and using the obtained weights to weight the received intermediate frequency signal to suppress continuous wave interference, and obtain output data after continuous wave interference suppression;

[0011] S4: Using a pulse suppression algorithm to suppress the pulses of the output data obtained in step S3, obtaining output data after both continuous wave interference and pulse interference are suppressed, thereby achieving joint suppression of continuous wave interference and pulse interference.

[0012] Preferably, the array antenna of the receiver in step S1 is an ideal uniform equidistant linear array composed of M array elements.

[0013] Preferably, the signal data processing process received by the M-element array antenna of the receiver in step S1 is that the signal passes through the RF channel, and the signal spectrum is moved from the RF to the analog intermediate frequency for down-frequency processing, the data is bandpass sampled through the A / D converter, and finally the analog intermediate frequency signal is converted into a digital intermediate frequency signal.

[0014] Preferably, the robust covariance matrix in step S2 is obtained by using an iterative method from the MK*1-dimensional snapshot signal obtained in step S1.

[0015] Preferably, the iterative equation for obtaining the robust covariance matrix in step S2 is as follows:

[0016]

[0017] Where x(n) is the snapshot data received by MK*1, R1 is the initial value of the iteration and the sample covariance estimation result, t is the number of iterations, R t+1is the covariance matrix estimation result after t+1 iterations.

[0018] Preferably, if the expected signal outlier value after the iteration is greater than the expected signal outlier value before the iteration, let t=t+1, continue the iteration, and repeat the calculation until the iteration terminates; if the expected signal outlier value after the iteration is less than or equal to the expected signal outlier value before the iteration, the iteration terminates, assuming that the iteration converges after the Tth time.

[0019] Preferably, the space-time two-dimensional minimum power algorithm in step S3 solves the weight equation as follows:

[0020]

[0021] swt H δ MK =1

[0022]

[0023] Among them, δ MK =[1,0,…,0] T , R T is the robust covariance matrix obtained in step S2, w is the weight, and R T The purpose of replacing the sample covariance estimate R1 in the space-time two-dimensional minimum power algorithm is to avoid the influence of pulse interference on the continuous wave interference suppression effect, thereby enhancing the continuous wave interference suppression effect.

[0024] Preferably, in step S4, for the output signal after continuous wave interference suppression, a robust interference suppression method is used to suppress pulse interference, and the formula is as follows:

[0025]

[0026] Where y(n) is the output signal after continuous wave interference suppression, γ T For a given threshold value, it can be set according to the noise power; ψ T (y(n)) is the output signal after pulse interference suppression.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention adopts a method of first suppressing continuous wave interference and then suppressing pulse interference. When using a space-time two-dimensional minimum power algorithm to suppress continuous wave interference, a robust covariance matrix estimation algorithm is used to replace a conventional sample covariance estimation algorithm, so as to eliminate the manifestation of pulse interference in the covariance matrix estimation result and avoid the influence of pulse interference on the continuous wave interference suppression performance. Then, for the remaining pulse interference after continuous wave suppression, a robust interference suppression algorithm is used to suppress the pulse interference. Compared with the existing method, when continuous wave interference and pulse interference exist at the same time, this method can improve the effect of continuous wave interference suppression and suppress one more continuous wave interference than the conventional space-time two-dimensional minimum power algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a flow chart of a robust continuous wave interference and pulse interference joint suppression method of the present invention;

[0030] Figure 2 It is a block diagram of a space-time two-dimensional anti-interference system consisting of M array elements and K time-domain taps;

[0031] Figure 3 It is the beam pattern corresponding to the minimum power weight after estimating the traditional sample covariance matrix in the case of continuous wave broadband interference and pulse interference;

[0032] Figure 4 The beam pattern obtained by using the method proposed by the present invention under the conditions of continuous wave broadband interference and pulse interference;

[0033] Figure 5 The beam pattern corresponding to the weights of the space-time two-dimensional minimum power algorithm is estimated using the traditional sample covariance matrix in the case of continuous wave narrowband interference and pulse interference;

[0034] Figure 6 This is the beam pattern obtained by using the method proposed in the present invention under the conditions of continuous wave broadband interference and pulse interference. DETAILED DESCRIPTION

[0035] 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 only 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 are within the scope of protection of the present invention.

[0036] See also Figure 1-6 The present invention provides a technical solution comprising the following steps:

[0037] S1: Process the signal received by the M-element array antenna of the receiver to obtain an intermediate frequency sampling signal, that is, a snapshot signal received in MK*1 dimensions, where K is the number of time domain taps;

[0038] S2: Using the MK*1-dimensional snapshot signal obtained in step S1 and the robust covariance matrix estimation method, the robust covariance matrix is ​​estimated and the proportion of pulse interference in the signal is reduced to improve the suppression effect of continuous wave interference. When continuous wave interference and pulse interference exist in the signal, for the sample covariance matrix, the pulse part can be regarded as an outlier of continuous wave interference, and the existence of these outliers will affect the weight corresponding to the continuous wave interference. The sample covariance matrix contains both pulse interference and continuous wave interference. Due to the insufficient number of array elements, the two interferences affect each other, and the required weights cannot effectively suppress any interference. Robust covariance matrix estimation is a type of M estimator, which removes outliers in the signal through continuous iteration, reduces the proportion of pulse interference in the signal, makes the required weights quasi-continuous wave interference, and improves the suppression effect of continuous wave interference. Its iterative equation is as follows:

[0039]

[0040] In the formula, x(n) is the snapshot data received by MK*1, and the initial value of R1 iteration is the sample covariance estimation result. t is the number of iterations, R t+1 is the covariance matrix estimation result after t+1 iterations. If the expected signal outlier value after the iteration is greater than the expected signal outlier value before the iteration, let t=t+1, continue the iteration, and repeat the calculation until the iteration terminates. If the expected signal outlier value after the iteration is less than or equal to the expected signal outlier value before the iteration, the iteration terminates. It is assumed that the iteration converges after the Tth iteration.

[0041] S3: Use the robust covariance matrix estimate obtained in step S2 to replace the covariance matrix estimate of the space-time two-dimensional minimum power algorithm, solve the optimal weight, and use the obtained weight to weight the received intermediate frequency signal to suppress continuous wave interference, and obtain the output data after continuous wave interference suppression. The space-time two-dimensional minimum power algorithm constrains the weight of the first element of the reference antenna to 1 based on the characteristics that the power of the satellite signal reaching the ground is low and the suppression interference power is usually strong, so as to minimize the array power output to obtain the weight. The weight equation is solved as shown below.

[0042]

[0043] swt H δ MK =1

[0044]

[0045] Among them, δ MK =[1,0,…,0] T , R T is the robust covariance matrix obtained in step S2, and w is the weight obtained. T Replacing the sample covariance estimate R1 in the space-time two-dimensional minimum power algorithm is to avoid the influence of pulse interference on the continuous wave interference suppression effect, thereby enhancing the continuous wave interference suppression effect;

[0046] S4: The pulse suppression algorithm is used to suppress the pulse of the output data obtained in step S3, and the output data after the continuous wave interference and the pulse interference are suppressed at the same time is obtained, so as to realize the joint suppression of the continuous wave interference and the pulse interference. The robust interference suppression method used for the residual pulse interference is used to normalize the amplitude of the pulse part exceeding the threshold, retain the signal phase information, reduce the signal loss, and process the signal after the continuous wave interference is suppressed. The formula is as follows:

[0047]

[0048] Where y(n) is the output signal after continuous wave interference suppression, γ T For a given threshold value, it can be set according to the noise power; ψ T (y(n)) is the output signal after pulse interference suppression.

[0049] The effect of the continuous wave and pulse interference joint suppression method based on robust covariance matrix estimation provided by the present invention can be further illustrated by the following simulation data experiment.

[0050] The simulation experiment takes two array elements as an example. A GPS signal simulator is used to generate GPS signals of two array elements, including 9 satellites: PRN4, PRN6, PRN8, PRN14, PRN15, PRN20, PRN25, PRN26, and PRN30. The sampling frequency is 15MHz. The direction, signal-to-noise ratio, and Doppler spectrum of each satellite are shown in Table 1:

[0051] Table 1

[0052]

[0053]

[0054] The suppression interference signal uses two kinds of mixed interference to carry out simulation experiments, namely the mixed interference of narrowband continuous wave and pulse and the mixed interference of broadband continuous wave and pulse. Among them, the narrowband interference comes from 40°, the interference-to-noise ratio is 40dB, and the interference signal frequency is 1575.72MHz; the broadband interference comes from -20°, the interference-to-noise ratio is 40dB; the pulse interference comes from 10°, the duty cycle is 15%, the pulse width is 3ms, and the interference-to-noise ratio is 43dB.

[0055] For the mixed interference of continuous wave broadband and pulse, the beam pattern obtained by using the traditional sample covariance matrix and space-time minimum power algorithm is as follows: Figure 3 As shown. Since the dual antenna cannot provide two spatial degrees of freedom to simultaneously suppress continuous wave broadband interference and pulse interference, the pulse interference and continuous wave broadband interference affect each other, and the corresponding beam pattern cannot form a null at any interference. When the proposed algorithm solves the optimal weight vector of the space-time minimum power algorithm, the robust covariance matrix estimate is used to replace the sample covariance matrix estimate. Among them, the robust covariance matrix estimation algorithm reduces the impact of pulse interference through continuous iterations in the process of estimating the covariance matrix, eliminates the manifestation of the pulse part in the covariance matrix, and avoids the impact of pulse interference on continuous wave interference suppression. The beam pattern corresponding to the proposed algorithm is shown as follows Figure 4 As shown in the figure, a null of about 90dB is formed at -20° from the wide interference source.

[0056] After suppressing the continuous wave interference, the complex mixed interference suppression problem can be optimized to the pulse interference suppression problem. The satellite tracking carrier-to-noise ratio after suppressing the interference using the space-time minimum power algorithm, the pulse interference suppression algorithm combining the space-time minimum power algorithm and the time domain zeroing, and the proposed algorithm are shown in Table 2. As can be seen from Table 2, the satellite cannot be tracked using the space-time minimum power algorithm and the pulse interference suppression algorithm with time domain zeroing, while the proposed method can track all satellites by eliminating the pulse influence. This shows that using the proposed algorithm, a two-element receiver can suppress a broadband interference and a pulse interference at the same time. The proposed algorithm is also applicable to array receivers with more than two elements.

[0057] Table 2

[0058]

[0059] For the mixed interference of continuous wave narrowband interference and pulse, the beam pattern using the traditional sample covariance matrix and space-time minimum power algorithm is as follows: Figure 5 As shown in Figure 2, the beam pattern using the proposed algorithm is shown in Figure 2. Figure 6 The method. Comparison Figure 5 and Figure 6 It can be seen that the traditional sample covariance matrix and space-time minimum power algorithm cannot form an effective null for any interference, while the proposed algorithm forms a deep null of about 100dB at 40° from the narrowband interference direction. After suppressing the continuous wave narrowband interference, the robust interference suppression method is used to suppress the pulse interference in the time domain. The tracking results of Algorithm 1, Algorithm 2 and the proposed algorithm after anti-interference are shown in Table 3. It can be seen from Table 3 that compared with other algorithms, the proposed algorithm can track more satellites and the signal quality is also significantly improved.

[0060] Table 3

[0061]

[0062]

[0063] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A robust method for joint suppression of continuous wave interference and pulse interference, characterized in that: The following steps are involved: S1: Process the signal received by the M-element array antenna of the receiver to obtain an intermediate frequency sampling signal, that is, a snapshot signal received in MK*1 dimensions, where K is the number of time domain taps; S2: using the MK*1-dimensional snapshot signal obtained in step S1 and adopting a robust covariance matrix estimation method, the robust covariance matrix is ​​estimated and the proportion of pulse interference in the signal is reduced to achieve the effect of improving the suppression of continuous wave interference; S3: using the robust covariance matrix estimate obtained in step S2 to replace the covariance matrix estimate of the space-time two-dimensional minimum power algorithm, solving the optimal weights, and using the obtained weights to weight the received intermediate frequency signal to suppress continuous wave interference, and obtain output data after continuous wave interference suppression; S4: Using a pulse suppression algorithm to suppress the pulses of the output data obtained in step S3, obtaining output data after both continuous wave interference and pulse interference are suppressed, thereby achieving joint suppression of continuous wave interference and pulse interference.

2. A robust continuous wave interference and pulse interference joint suppression method according to claim 1, characterized in that: The array antenna of the receiver in step S1 is an ideal uniform equidistant linear array composed of M array elements.

3. A robust continuous wave interference and pulse interference joint suppression method according to claim 1, characterized in that: The signal data processing process received by the M-element array antenna of the receiver in step S1 is as follows: the signal passes through the RF channel, and the signal spectrum is moved from the RF to the analog intermediate frequency for down-frequency processing, the data is bandpass sampled by the A / D converter, and finally the analog intermediate frequency signal is converted into a digital intermediate frequency signal.

4. A robust continuous wave interference and pulse interference joint suppression method according to claim 1, characterized in that: The robust covariance matrix in step S2 is obtained by using an iterative method from the MK*1-dimensional snapshot signal obtained in step S1.

5. A robust continuous wave interference and pulse interference joint suppression method according to claim 4, characterized in that: The iterative equation for obtaining the robust covariance matrix in step S2 is as follows: Where x(n) is the snapshot data received by MK*1, R1 is the initial value of the iteration and the sample covariance estimation result, t is the number of iterations, R t+1 is the covariance matrix estimation result after t+1 iterations.

6. A robust continuous wave interference and pulse interference joint suppression method according to claim 5, characterized in that: In the iterative equation for obtaining the robust covariance matrix in step S2, if the expected signal outlier value after iteration is greater than the expected signal outlier value before iteration, set t=t+1, continue iteration, and repeat calculation until the iteration terminates; if the expected signal outlier value after iteration is less than or equal to the expected signal outlier value before iteration, the iteration terminates, assuming that the iteration converges after the Tth time.

7. A robust continuous wave interference and pulse interference joint suppression method according to claim 1, characterized in that: The space-time two-dimensional minimum power algorithm in step S3 solves the weight equation as follows: s.t.w H δ MK =1 Among them, δ MK =[1,0,…,0] T , R T is the robust covariance matrix obtained in step S2, w is the weight, and R T The purpose of replacing the sample covariance estimate R1 in the space-time two-dimensional minimum power algorithm is to avoid the influence of pulse interference on the continuous wave interference suppression effect, thereby enhancing the continuous wave interference suppression effect.

8. A robust continuous wave interference and pulse interference joint suppression method according to claim 1, characterized in that: In step S4, the pulse interference is suppressed by using a robust interference suppression method for the output signal after continuous wave interference suppression, and the formula is as follows: Where y(n) is the output signal after continuous wave interference suppression, γ T For a given threshold value, it can be set according to the noise power; ψ T (y(n)) is the output signal after pulse interference suppression.

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