Random channel fault-oriented anti-interference adaptive degradation method

Abstract

The invention belongs to the field of satellite navigation, and particularly relates to a random channel fault-oriented anti-interference adaptive degradation method, which comprises the following steps of: realizing channel power estimation and fault detection through intermediate frequency data; judging whether the reference main array element has a fault or not through the fault list; an array with the best satellite receiving condition is set as a temporary reference main array, and meanwhile, a constraint vector is adjusted to carry out weight calculation and weighted filtering; dynamic optimization and cyclic detection are set to realize adaptive tracking of channel faults and self-recovery of an anti-interference algorithm after the faults are cleared. According to the method, a fixed main array is not set in an anti-interference algorithm, and the temporary reference main array is adaptively adjusted by performing periodic detection on the channel fault, so that the anti-interference adaptive degradation capability after the channel fault is realized, and the robustness of an anti-interference receiver facing the random channel fault is effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of satellite navigation, specifically relating to an anti-interference adaptive degradation method for random channel faults. Background Technology

[0002] As the electromagnetic environment of modern battlefields becomes increasingly complex and the intensity of electronic warfare continues to escalate, array antennas are becoming larger and larger to meet operational requirements such as suppressing multi-directional interference and resisting broadband suppression of jamming signals. The number of accompanying radio frequency channels is also increasing by a similar margin. However, in real-world combat scenarios, antenna arrays or radio frequency channels are susceptible to localized unit failures due to harsh battlefield factors such as high-power jamming signals, extreme temperature variations, equipment overload, and complex electromagnetic coupling effects.

[0003] Currently, conventional power inversion algorithms and minimum variance distortion-free response algorithms in anti-interference receivers all require the setting of fixed main array elements and the provision of reliable reference signals. Once the main array element loses its function due to hardware damage or link interruption, the entire algorithm will lose its beamforming reference, resulting in a precipitous drop in interference suppression performance, a deterioration in the interference-to-signal ratio of the navigation receiver, and the complete suppression of satellite navigation signals by interference. Summary of the Invention

[0004] In view of this, the present invention aims to provide an anti-interference adaptive degradation method for random channel failures, so that when the antenna array or radio frequency channel fails, the anti-interference receiver can achieve adaptive degradation and has a certain anti-interference capability.

[0005] This application provides an anti-interference adaptive degradation method for random channel faults, the method comprising the following steps:

[0006] Step (1): Channel power estimation and fault detection. The channel power is estimated by the moving average method, and the fault channel number is output.

[0007] Step (2): Summarize fault information and judge the fault of the reference main array element; if the reference main array element has not failed, the constraint vector is the preset value and remains unchanged, and proceed to step (4); if the reference main array element has failed, proceed to step (3);

[0008] Step (3): Temporary reference master array element setting and constraint vector adjustment;

[0009] Step (4): Weight calculation and weighted filtering: Calculate weights based on the constraint vector and perform weighted filtering on the intermediate frequency data to achieve anti-interference effect.

[0010] Step (5): Loop detection and dynamic optimization.

[0011] Furthermore, in step (1), the intermediate frequency data after downconversion is acquired by AD, and the power of the M channels is estimated using the moving average method. The specific power estimation formula is as follows:

[0012]

[0013] Among them, P i This represents the power of the i-th channel. Let N be the intermediate frequency sampled signal of the i-th channel, N be the sampling window length, t be the current time, and n be the sampling delay time.

[0014] Further, in step (2), assuming the reference main array element is the j-th array element, if the reference main array element does not fail, it means that the reference main array element is still usable. In order to reduce the control complexity of the system, the constraint vector should remain unchanged at the preset value, that is, the j-th element of the constraint vector is 1 and the rest of the elements are zero, and then proceed to step (4); if the reference main array element fails, then proceed to step (3).

[0015] Furthermore, in step (3):

[0016] First, analyze the satellite reception of the remaining intact channels based on their channel power to assess the signal quality of each channel; the specific formula is as follows:

[0017]

[0018]

[0019] in This indicates the maximum power of all channels. Indicates the array element number where the maximum power is located;

[0020] Next, select the array element with the best satellite signal quality. Set as a temporary reference main array;

[0021] Finally, adjust the constraint vectors by setting the position of the temporary reference main matrix of the constraint vectors to 1 and the rest to 0.

[0022] Furthermore, in step (5), a dynamic optimization period T is set to periodically recalculate the power and signal quality to achieve adaptive tracking; if the faulty channel is restored, the original reference main array element is re-evaluated to ensure anti-interference performance and realize the self-recovery capability of the anti-interference algorithm after fault clearance.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0024] (1) This invention can detect faulty channels in a timely manner by monitoring the power of each channel in real time, and dynamically adjust the reference main array element according to the fault situation. This method not only improves the anti-interference capability of the system, but also enhances the reliability and adaptability of the system. In addition, this invention does not set a fixed main array in the anti-interference algorithm, eliminating the dependence of main array element / main channel, and significantly reducing the sensitivity of interference suppression performance to the fault of a single array element.

[0025] (2) When the antenna array or radio frequency channel fails, the anti-interference algorithm does not need to be adjusted when the non-reference main array element fails, and the adaptive degradation control can be achieved. The system's fault-tolerant control algorithm has low complexity.

[0026] (3) Through periodic dynamic optimization and feedback, the anti-interference algorithm can adaptively recover when the radio frequency channel has a non-permanent fault or when the fault is being repaired, thereby ensuring the anti-interference performance of the device. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a schematic diagram of the workflow of the present invention; Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] This invention proposes an anti-interference adaptive degradation method for random channel failures, which enables the anti-interference receiver to adaptively degrade and has a certain anti-interference capability when the antenna array or radio frequency channel fails.

[0031] like Figure 1 As shown, this invention proposes a space-frequency anti-interference method based on adaptive null broadening, comprising the following steps:

[0032] Step (1): Channel power estimation and fault detection.

[0033] (1.1) The intermediate frequency data after downconversion is acquired by the AD sampling circuit, thereby estimating the power of the M channels and calculating the current power P of each channel. i (i=1,2,…,M), where P i This represents the power of the i-th channel, where i is the channel number and M represents the number of channels.

[0034] Power estimation can be achieved using the moving average method:

[0035]

[0036] in, Let N be the intermediate frequency sampled signal of the i-th channel, N be the sampling window length, t be the current time, and n be the sampling delay time.

[0037] (1.2) When the power of a certain channel is less than the preset value P set This indicates that the channel has only radio frequency noise floor, signifying a channel failure, and outputs the fault channel number to provide fault information for the implementation of subsequent anti-interference algorithms.

[0038] Step (2): Summarize fault information and judge faults of reference main array elements.

[0039] (2.1) Summarize all channel fault information and generate a fault list F={F1, F2, ..., F...} K (K is the number of faulty channels);

[0040] (2.2) Check if the reference master array element is in the fault list;

[0041] (2.3) Perform conditional judgment: First, assume that the reference main array element is the j-th array element. If the reference main array element has not failed, it means that the reference main array element is still usable. In order to reduce the control complexity of the system, the constraint vector should remain unchanged at the preset value, that is, the j-th element of the constraint vector is 1 and the rest of the elements are zero, and proceed to step (4). If the reference main array element fails, proceed to step (3). The advantage of this step is that when the reference main array element has not failed, the anti-interference algorithm does not need to be adjusted to achieve adaptive degradation control, and the fault-tolerant control algorithm of the system has low complexity.

[0042] Step (3): Temporary reference master array element setting and constraint vector adjustment.

[0043] First, analyze the satellite reception of the remaining intact channels based on their channel power to assess the signal quality of each channel. The specific formula is as follows:

[0044]

[0045]

[0046] in This indicates the maximum power of all channels. This indicates the array element number where the maximum power is located.

[0047] Next, select the array element with the best satellite signal quality. Set as a temporary reference main array;

[0048] Finally, adjust the constraint vector, setting the position of the temporary reference main array to 1 and the rest to 0. The key design point of this step is that no fixed main array element is set in the anti-interference algorithm. When the main array element fails to transmit, a temporary reference main array is immediately set to replace it. This eliminates the dependence of the anti-interference algorithm on the main array element / main channel and greatly reduces the sensitivity of the interference suppression performance to the failure of a single array element.

[0049] Step (4): Weight calculation and weighted filtering.

[0050] Weights are calculated based on constraint vectors, and intermediate frequency data is weighted and filtered to achieve anti-interference effect.

[0051] Step (5): Loop detection and dynamic optimization.

[0052] First, a cyclic detection period T is set, which periodically recalculates the signal power of all channels to achieve periodic monitoring of channel signals. Then, a dynamic optimization scheme is adopted. When the channel power changes, a temporary reference to the main array is used for dynamic optimization; that is, when the original main array channel power exceeds a preset value P... set At this point, the original reference main array element should be switched back to ensure anti-interference performance and realize the self-recovery capability of the anti-interference algorithm after fault clearing.

[0053] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0054] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for anti-interference adaptive degradation for random channel faults, characterized in that, Includes the following steps: Step (1): Channel power estimation and fault detection. The channel power is estimated by the moving average method, and the fault channel number is output. Step (2): Summarize fault information and determine faults in the reference main array element; If the reference master element does not fail, the constraint vector remains unchanged at the preset value, and the process proceeds to step (4); if the reference master element fails, the process proceeds to step (3). Step (3): Temporary reference master array element setting and constraint vector adjustment; Step (4): Weight calculation and weighted filtering: Calculate the weights based on the constraint vector and perform weighted filtering on the intermediate frequency data to achieve anti-interference effect; Step (5): Loop detection and dynamic optimization.

2. The anti-interference adaptive degradation method for random channel faults according to claim 1, characterized in that, In step (1), the intermediate frequency data after downconversion is acquired by AD, and the power of M channels is estimated by the moving average method. The specific power estimation formula is as follows: ； Among them, P i This represents the power of the i-th channel. Let N be the intermediate frequency sampled signal of the i-th channel, N be the sampling window length, t be the current time, and n be the sampling delay time.

3. The anti-interference adaptive degradation method for random channel faults according to claim 1, characterized in that, In step (2), assuming the reference master array element is the j-th array element, if the reference master array element does not fail, it means that the reference master array element is still usable at this time. In order to reduce the control complexity of the system, the constraint vector should remain unchanged at the preset value, that is, the j-th element of the constraint vector is 1 and the rest of the elements are zero, and then proceed to step (4); if the reference master array element fails, then proceed to step (3).

4. The anti-interference adaptive degradation method for random channel faults according to claim 1, characterized in that, In step (3): First, analyze the satellite reception of the remaining intact channels based on their channel power to assess the signal quality of each channel; the specific formula is as follows: ； ； in This indicates the maximum power of all channels. Indicates the array element number where the maximum power is located; Next, select the array element with the best satellite signal quality. Set as a temporary reference main array; Finally, adjust the constraint vectors by setting the position of the temporary reference main matrix of the constraint vectors to 1 and the rest to 0.

5. The anti-interference adaptive degradation method for random channel faults according to claim 1, characterized in that, In step (5), a dynamic optimization period T is set to periodically recalculate power and signal quality to achieve adaptive tracking; If the faulty channel is restored, reassess whether to switch back to the original reference main array element to ensure anti-interference performance and realize the self-recovery capability of the anti-interference algorithm after the fault is cleared.

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