Self-adaptive beam keeping method for local fault removal channel

Abstract

The invention discloses a local fault removal channel adaptive beam keeping method. According to the method, the optimal amplitude and phase of the remaining normal channels are adaptively optimized through the fault channel information fed back by the radar monitoring link, the influence of the fault channel is removed, the stability of indexes such as beam width and side lobe suppression is maintained, and the application requirements of the meteorological field are met.

Description

Technical Field

[0001] The invention relates to antenna and microwave technology, in particular to a channel adaptive beam keeping method for removing local faults. Background Art

[0002] Phased array radar has been fully utilized in various military and civilian fields due to its unique advantages such as multiple functions, strong mobility, short response time, high data rate, strong anti-interference ability and high reliability. In the field of meteorological radar, phased array radar can greatly reduce the radar scanning time and greatly improve the early warning capability of short-term and small-scale convective weather. This makes phased array radar widely favored in the meteorological field.

[0003] However, weather detection requires the known beam width of the radar, which requires the radar to maintain a stable beam width and relatively high sidelobe suppression during operation. Although the high reliability of phased array radar enables it to work stably even when some channels on the array face fail, damage to some channels on the array face will inevitably lead to deterioration of the radar beam. How to eliminate the limitation of its application in the meteorological field caused by the beam deterioration under the state of partial channel failure is an urgent problem to be solved.

[0004] The patent application with application number 202011044199.X discloses a beamforming simulation design method based on genetic algorithm. This method forms a target beam limited between two constraint lines through continuous iterative optimization, achieving a 40° wide beam cosecant square beamforming pattern.

[0005] However, this optimization method cannot be used when there is a faulty channel on the array, and cannot meet the meteorological requirements of maintaining a stable beam width and relatively high sidelobe suppression when some channels on the array fail.

[0006] In summary, it is urgent to incorporate the faulty channel into the beamforming algorithm and form an adaptive beam-keeping algorithm for the localized fault-free channel to meet the demand for stable beam shape in the meteorological field. Summary of the invention

[0007] In view of the problems existing in the prior art, the present invention provides a method for adaptive beam keeping of a localized faulty channel. The method adaptively optimizes the optimal amplitude and phase of the remaining normal channels through the faulty channel information fed back by the radar monitoring link, removes the influence of the faulty channel, maintains the stability of indicators such as beam width and sidelobe suppression, and meets the application requirements in the meteorological field.

[0008] The purpose of the present invention is achieved through the following technical solutions.

[0009] A channel adaptive beam keeping method for removing local faults includes the following design steps:

[0010] Step 1: Obtain radar array fault channel information through radar internal and external monitoring methods;

[0011] Step 2: Establish an evolution target, which specifies the maximum and minimum values ​​of the radar beam;

[0012] Step 3: Substitute the fault channel information to establish the first generation population, and set the gene values ​​corresponding to the fault channels of all individuals in the first generation population to zero; the first generation population is represented by P n {g i}; i∈[1…M]; n∈[1…N], where g i Indicates the gene value corresponding to the amplitude and phase information of each channel. The gene value corresponding to the faulty channel is set to zero, that is, the corresponding g i =0, the population size is N, P n is the nth individual, with M genes;

[0013] Step 4: Establish the fitness function C=lg(∑max(DF,0)+∑max(FU,0)) according to the array characteristics, where U and D are the upper and lower limits of the evolution target, respectively, and F is the array radiation beam result calculated by the individuals in the population;

[0014] Step 5: Evaluate the fitness of the first generation population, score and rank each individual;

[0015] Step 6: Set up a selection area, randomly select the father and mother individuals in the selection area, and randomly select the gene breakpoints, exchange the gene fragments of the father and mother individuals, and generate a pair of child individuals;

[0016] Step 7: Set the gene mutation factor c, the maximum gene mutation range R, and the gene mutation range △ = R (e -δt -e -δ ), where t is the evolution time; randomly mutate the number and position of genes, and in this process, set the mutation amount of the gene position corresponding to the faulty channel to zero; that is, lock the gene corresponding to the faulty channel so that it does not mutate during evolution;

[0017] Step 8: Generate a corresponding number of offspring individuals according to the number of pairings, and score and sort the offspring population together with the parent population for fitness, and select and retain only the number of individuals specified by the population size, which is the population size N here;

[0018] Step 9: Repeat the evolution process until the specified number of evolutions is reached or the beam result corresponding to the best individual fully meets the evolution goal;

[0019] Step 10: Verify whether the obtained channel amplitude and phase meet the beam keeping requirements.

[0020] In the step 1, the radar array fault channel information is obtained by means of internal and external monitoring of the radar, and the fault channel information includes the location of the fault channel. All fault channels do not radiate energy during use.

[0021] In the step 2, an evolution target is established, and the evolution target can constrain indicators such as beam width and side lobe. The evolution target is carried out according to the indicator requirements. The purpose of the evolution is to make the beam achieve high side lobe suppression while ensuring that the beam width remains unchanged, or to ensure the highest side lobe suppression for the beam and feedback the beam width.

[0022] In step 3, the fault channel information is substituted to establish the first generation population P n {g i}; i∈[1…M]; n∈[1…N], the information of g0 is obtained from the fault channel information obtained in step 1, the number of genes M is determined by the number of channels in the array, and the number of populations N is set by the accuracy and speed required by the algorithm.

[0023] In the step 4, a fitness function is established, and the number of calculation points of the optimization target upper limit U and lower limit D and the radiation beam result F are the same, and are mapped one-to-one with the spatial domain angle.

[0024] In the step six, a preferential selection area is set, and the preferential selection area is the selection range for selecting parent individuals. According to the fitness score, a preferred range is defined, and the range is adjustable; gene breakpoints are randomly selected, and the number of gene breakpoints is adjustable, that is, the position and number of times of exchange of parent individual gene fragments can be performed at multiple random positions.

[0025] In step 7, the gene variation factor c, the maximum gene variation range R, and the gene variation range are set.

[0026] △=R(e -δt -e -δ ), where t is the evolution time, the gene mutation factor c and the maximum gene mutation range R are constants and adjustable, which determine the degree of mutation; the gene variation range is the amount that decreases as the evolution time increases, and the evolution time corresponds to the number of evolutions in the algorithm; the mutation amount of the gene position corresponding to the faulty channel is set to zero: the corresponding gene mutation amount is set to zero through the faulty channel information obtained in step 1, that is, to ensure that during the evolution process, the gene value corresponding to the faulty channel is always zero and does not participate in the evolution process.

[0027] The step nine is performed until the specified number of evolutions is reached or the beam result corresponding to the best individual fully meets the evolution target. The evolution result is not unique. This step can be performed multiple times to obtain multiple different evolution results.

[0028] In the step 10, it is verified whether the channel amplitude and phase obtained by the algorithm meets the beam keeping requirements. The channel amplitude and phase results obtained by the algorithm must meet the amplitude and phase quantization requirements of each radar channel, and are applied to the actual radar array. The beam results after the amplitude and phase quantization of each channel are verified by electromagnetic simulation software; steps 3 to 9 are performed multiple times to verify and take the optimal result among the evolution results in step 9.

[0029] Compared with the prior art, the advantages of the present invention are: 1. The array beam holding function is completed within the array failure rate range through the channel adaptive algorithm for delocalizing failures, thereby ensuring the high reliability, high stability and high effectiveness of the array in a low-cost manner.

[0030] 2. The array beam can be optimized by simply using the fault channel information fed back by the internal and external monitoring functions. It can be applied in various fault rate ranges and has a wide range of applicable faults.

[0031] 3. During the beam holding process, the beam width of the array beam is guaranteed to remain unchanged and the side lobes are highly suppressed, fully meeting the application requirements of meteorological radar. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the present invention.

[0033] Figure 2 This is the optimization process and results of the 3% channel random failure in the embodiment of the present invention.

[0034] Figure 3 This is a beam comparison between a beam with 1% channel random failure and a beam without failure in an embodiment of the present invention.

[0035] Figure 4 This is a beam comparison between a beam with 3% channel random failure and a beam without failure in an embodiment of the present invention.

[0036] Figure 5 This is a comparison between the beam with 5% channel random failure situation 1 and a beam without failure in the embodiment of the present invention.

[0037] Figure 6 This is a comparison between the beam with 5% channel random failure situation 2 and a beam without failure in the embodiment of the present invention.

[0038] Figure 7 This is a beam comparison of 1% channel random failure and repair failure in the embodiment of the present invention.

[0039] Figure 8 This is the amplitude and phase distribution result of each channel after the 1% channel random fault is repaired in the embodiment of the present invention.

[0040] Fig. 9 This is the beam comparison of 3% channel random fault and repair fault in the embodiment of the present invention.

[0041] Fig.10 This is the amplitude and phase distribution result of each channel after the 3% channel random fault is repaired in the embodiment of the present invention.

[0042] Fig.11 This is a beam comparison of 5% channel random failure situation 1 and the repaired failure in the embodiment of the present invention.

[0043] Fig.12 This is the amplitude and phase distribution result of each channel after repair in the 5% channel random fault situation 1 in the embodiment of the present invention.

[0044] Fig.13 This is a beam comparison of 5% channel random fault situation 2 and the repaired fault in the embodiment of the present invention.

[0045] Fig.14 This is the amplitude and phase distribution result of each channel after repair in the 5% channel random fault situation 2 in the embodiment of the present invention.

[0046] Fig.15 This is a beam comparison of repairing faults in all fault situations in the embodiments of the present invention. DETAILED DESCRIPTION

[0047] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0048] like Figure 1 As shown, a method for adaptive beam keeping of a channel for removing local faults comprises the following steps. In this embodiment, a linear array composed of 160 units is taken as an example. The index requires that the beam width is kept at 1 degree under the condition of a maximum of 5% random channel faults, and the sidelobe suppression is as high as possible. The embodiments are respectively set to 1% random channel faults, 3% random channel faults, and 5% random channel faults in two cases:

[0049] Step 1: Obtain radar array fault channel information through internal and external monitoring means; in this embodiment, 1% random fault channels are the 18th and 71st channels; 3% random fault channels are the 37th, 59th, 64th, 74th and 122nd channels; 5% random fault channel situation 1 is the 15th, 65th, 90th, 94th, 117th, 118th, 128th and 156th channels; 5% random fault channel situation 2 is the 5th, 30th, 32nd, 53rd, 83rd, 86th, 108th and 158th channels.

[0050] Step 2: Establish an evolution target, which specifies the maximum and minimum values ​​of the radar beam. In this embodiment, the maximum value of the beam within the range of ±0.5° is specified as 0 dB, and the minimum value is specified as -3 dB.

[0051] Step 3: Substitute the fault channel information to establish the first generation population, and set the gene values ​​corresponding to the fault channels of all individuals in the first generation population to zero. The first generation population is represented by P n {g i}; i∈[1…M]; n∈[1…N], where g i Indicates the gene value corresponding to the amplitude and phase information of each channel. The gene value corresponding to the faulty channel is set to zero, that is, the corresponding g i =0, in this embodiment, the gene value of the corresponding fault channel position in step 1 is set to zero. The population size is N = 100, P n It is the nth individual, and the number of genes is M=160.

[0052] Step 4: Establish the evaluation function C = lg(∑max(DF,0)+∑max(FU,0)) of 160 units, where U and D are the upper and lower limits of the evolution target, respectively, and F is the front radiation beam result calculated by the individuals in the population.

[0053] Step 5: Evaluate the fitness of the first generation population, score and rank each individual.

[0054] Step 6: Set the selection area to 10, randomly select the father and mother individuals from the top 10 individuals, randomly select the gene breakpoints, exchange the gene fragments of the father and mother individuals, and generate a pair of child individuals.

[0055] Step 7: Set the gene mutation factor c = 1.5, the maximum gene mutation range R = 0.2, and the gene mutation range △ = R (e -δt -e -δ ), where t is the evolution time. Randomly mutate the number and position of genes. In this process, the mutation amount of the gene position corresponding to the faulty channel is set to zero. That is, the gene corresponding to the faulty channel is locked so that it does not mutate during evolution.

[0056] Step 8: Generate a corresponding number of offspring individuals according to the number of pairings, and the number of pairings is set to 25. The offspring population and the parent population are scored and sorted for fitness, and only the number of individuals specified by the population size is selected and retained, which is the population size N here.

[0057] Step 9: Repeat the evolution process until the specified number of evolutions is reached or the beam result corresponding to the best individual fully meets the evolution target. The optimization process and results of 3% channel random failures are shown in the figure. Figure 2 shown.

[0058] Step 10: Verify whether the obtained channel amplitude and phase meet the beam keeping requirements.

[0059] In the step 1, the radar array fault channel information is obtained by means of internal and external monitoring of the radar, and the fault channel information includes the location of the fault channel. All fault channels do not radiate energy during use.

[0060] In the step 2, an evolution target is established, and the evolution target can constrain indicators such as beam width and side lobe. The evolution target is carried out according to the indicator requirements. The purpose of the evolution is to make the beam achieve high side lobe suppression while ensuring that the beam width remains unchanged, or to ensure the highest side lobe suppression for the beam and feedback the beam width.

[0061] In step 3, the fault channel information is substituted to establish the first generation population P n {g i}; i∈[1…M]; n∈[1…N], the information of g0 is obtained from the fault channel information obtained in step 1, the number of genes M is determined by the number of channels in the array, and the number of populations N is set by the accuracy and speed required by the algorithm.

[0062] In the step 4, a fitness function is established, and the number of calculation points of the optimization target upper limit U and lower limit D and the radiation beam result F are the same, and are mapped one-to-one with the spatial domain angle.

[0063] In the step six, a preferential selection area is set, and the preferential selection area is the selection range for selecting parent individuals. According to the fitness score, a preferred range is defined, and the range is adjustable; gene breakpoints are randomly selected, and the number of gene breakpoints is adjustable, that is, the position and number of times of exchange of parent individual gene fragments can be performed at multiple random positions.

[0064] In step 7, the gene variation factor c, the maximum gene variation range R, and the gene variation range are set.

[0065] △=R(e -δt -e -δ ), where t is the evolution time, the gene mutation factor c and the maximum gene mutation range R are constants and adjustable, which determine the degree of mutation; the gene variation range is the amount that decreases as the evolution time increases, and the evolution time corresponds to the number of evolutions in the algorithm; the mutation amount of the gene position corresponding to the faulty channel is set to zero: the corresponding gene mutation amount is set to zero through the faulty channel information obtained in step 1, that is, to ensure that during the evolution process, the gene value corresponding to the faulty channel is always zero and does not participate in the evolution process.

[0066] The step nine is performed until the specified number of evolutions is reached or the beam result corresponding to the best individual fully meets the evolution target. The evolution result is not unique. This step can be performed multiple times to obtain multiple different evolution results.

[0067] In the step 10, it is verified whether the channel amplitude and phase obtained by the algorithm meets the beam keeping requirements. The channel amplitude and phase results obtained by the algorithm must meet the amplitude and phase quantization requirements of each radar channel, and are applied to the actual radar array. The beam results after the amplitude and phase quantization of each channel are verified by electromagnetic simulation software; steps 3 to 9 are performed multiple times to verify and take the optimal result among the evolution results in step 9.

[0068] Figure 3 The beam comparison of 1% channel random fault and no fault is shown. At this time, the beam width changes from 1° to 0.99°, and the sidelobe suppression deteriorates from 40dB to 32.5dB. Figure 4 The beam comparison of 3% channel random faults and no faults is shown. At this time, the beam width changes from 1° to 0.98°, and the sidelobe suppression deteriorates from 40dB to 26.9dB. Figure 5 The comparison between the beams of case 1 with 5% channel random faults and a fault-free beam is shown. In this case, the beam width changes from 1° to 0.99°, and the sidelobe suppression deteriorates from 40dB to 26.0dB. Figure 6 The comparison between the beam in case 2 with 5% random channel failure and the beam without failure is shown. In this case, the beam width changes from 1° to 0.98°, and the sidelobe suppression deteriorates from 40dB to 25.16dB. It can be seen that as the number of channel failures increases, the sidelobe suppression deteriorates significantly.

[0069] Figure 7 The beam comparison of 1% random channel failure and the beam after the failure is repaired is shown. After the repair, the beam width is 1°, the sidelobe suppression is 35dB, and the optimized amplitude and phase distribution results of each channel are shown in Figure 8 shown. Fig. 9 The beam comparison of 3% random channel failure and after the failure is repaired is shown. After the repair, the beam width is 1°, the sidelobe suppression is 30dB, and the optimized amplitude and phase distribution results of each channel are shown in Fig.10 shown. Fig.11 The beam comparison of 5% random channel fault case 1 and the beam after fault repair is shown. After repair, the beam width is 1°, the sidelobe suppression is 30dB, and the optimized amplitude and phase distribution results of each channel are shown as follows: Fig.12 shown. Fig.13 The beam comparison of 5% random channel fault case 2 and the beam after fault repair is shown. After repair, the beam width is 1°, the sidelobe suppression is 30dB, and the optimized amplitude and phase distribution results of each channel are as follows: Fig.14 shown.

[0070] The repaired beams under various fault conditions are as follows: Fig.15 As shown, it can be seen that after each fault condition is repaired, the beam width maintains high consistency, and the side lobe is also extremely suppressed when the beam width is highly consistent.

[0071] The present invention effectively maintains the beam generated by the array within the failure rate range and without replacing the array components. In the use of the weather radar, the high reliability, high stability and high effectiveness of the phased array radar are guaranteed in a lowest cost manner.

Claims

1. A channel adaptive beam keeping method for removing local faults, characterized in that The design steps include: Step 1: Obtain radar array fault channel information through radar internal and external monitoring methods; Step 2: Establish an evolution target, which specifies the maximum and minimum values ​​of the radar beam; Step 3: Substitute the fault channel information to establish the first generation population, and set the gene values ​​corresponding to the fault channels of all individuals in the first generation population to zero; the first generation population is represented by P n {g i }; i∈[1…M]; n∈[1…N], where g i Indicates the gene value corresponding to the amplitude and phase information of each channel. The gene value corresponding to the faulty channel is set to zero, that is, the corresponding g i =0, the population size is N, P n is the nth individual, with M genes; Step 4: Establish the fitness function C=lg(∑max(DF,0)+∑max(FU,0)) according to the array characteristics, where U and D are the upper and lower limits of the evolution target, respectively, and F is the array radiation beam result calculated by the individuals in the population; Step 5: Evaluate the fitness of the first generation population, score and rank each individual; Step 6: Set up a selection area, randomly select the father and mother individuals in the selection area, and randomly select the gene breakpoints, exchange the gene fragments of the father and mother individuals, and generate a pair of child individuals; Step 7: Set the gene mutation factor c, the maximum gene mutation range R, and the gene mutation range △ = R (e -δt -e -δ ), where t is the evolution time; randomly mutate the number and position of genes, and in this process, set the mutation amount of the gene position corresponding to the faulty channel to zero; that is, lock the gene corresponding to the faulty channel so that it does not mutate during evolution; Step 8: Generate a corresponding number of offspring individuals according to the number of pairings, and score and sort the offspring population together with the parent population for fitness, and select and retain only the number of individuals specified by the population size, which is the population size N here; Step 9: Repeat the evolution process until the specified number of evolutions is reached or the beam result corresponding to the best individual fully meets the evolution goal; Step 10: Verify whether the obtained channel amplitude and phase meet the beam keeping requirements.

2. The method for adaptive beam keeping of a channel for removing local faults according to claim 1 is characterized in that In the step 1, the radar array fault channel information is obtained by means of internal and external monitoring of the radar, and the fault channel information includes the location of the fault channel. All fault channels do not radiate energy during use.

3. The method for adaptive beam keeping of a channel for removing local faults according to claim 1, characterized in that In the step 2, an evolution target is established, and the evolution target can constrain indicators such as beam width and side lobe. The evolution target is carried out according to the indicator requirements. The purpose of the evolution is to make the beam achieve high side lobe suppression while ensuring that the beam width remains unchanged, or to ensure the highest side lobe suppression for the beam and feedback the beam width.

4. The method for adaptive beam keeping of a channel for removing local faults according to claim 1, characterized in that In step 3, the fault channel information is substituted to establish the first generation population P n {g i }; i∈[1…M]; n∈[1…N], the information of g0 is obtained from the fault channel information obtained in step 1, the number of genes M is determined by the number of channels in the array, and the population size N is set by the accuracy and speed required by the algorithm.

5. The method for adaptive beam keeping of a channel for removing local faults according to claim 1, characterized in that In the step 4, a fitness function is established, and the number of calculation points of the optimization target upper limit U and lower limit D and the radiation beam result F are the same, and are mapped one-to-one with the spatial domain angle.

6. The method for adaptive beam keeping of a channel for removing local faults according to claim 1, characterized in that In the step six, a preferential selection area is set, and the preferential selection area is the selection range for selecting parent individuals. According to the fitness score, a preferred range is defined, and the range is adjustable; gene breakpoints are randomly selected, and the number of gene breakpoints is adjustable, that is, the position and number of times of exchange of parent individual gene fragments can be performed at multiple random positions.

7. The method for adaptive beam keeping of a channel for removing local faults according to claim 1, characterized in that In step 7, the gene variation factor c, the maximum gene variation range R, and the gene variation range △=R(e -δt -e -δ ), where t is the evolution time, the gene mutation factor c and the maximum gene mutation range R are constants and adjustable, which determine the degree of mutation; the gene variation range is the amount that decreases as the evolution time increases, and the evolution time corresponds to the number of evolutions in the algorithm; the mutation amount of the gene position corresponding to the faulty channel is set to zero: the corresponding gene mutation amount is set to zero through the faulty channel information obtained in step 1, that is, to ensure that during the evolution process, the gene value corresponding to the faulty channel is always zero and does not participate in the evolution process.

8. The method for adaptive beam keeping of a channel for removing local faults according to claim 1, characterized in that The step nine is performed until the specified number of evolutions is reached or the beam result corresponding to the best individual fully meets the evolution target. The evolution result is not unique. This step can be performed multiple times to obtain multiple different evolution results.

9. The method for adaptive beam keeping of a channel for removing local faults according to claim 1, characterized in that In the step 10, the channel amplitude and phase obtained by the verification algorithm meets the beam keeping requirements. The channel amplitude and phase results obtained by the algorithm need to meet the amplitude and phase quantization requirements of each channel of the radar, and are applied to the actual radar array. The beam results after the amplitude and phase quantization of each channel are verified by electromagnetic simulation software; Perform steps three to nine multiple times, verify and take the best result from the evolution results in step nine.

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