阅读说明：本技术 一种应用于宽带天线阵列在时域进行校准的方法 (Method for calibrating broadband antenna array in time domain ) 是由 张永伟 施佺 吕先洋 邢慧娟 许致火 施佳佳 付艳伟 于 2021-08-31 设计创作，主要内容包括：本发明公开了一种应用于宽带天线阵列在时域进行校准的方法,包括天线阵列在时域进行校准、根据天线数量确定的时延范围,运用同时扰动随机估计(SPSA)算法,分别以P-(in)与P-(k)之差与P-(in)之比和1-R-(k)作为损失函数,优化得到目标时延,该算法可直接应用于宽带天线阵列的校准,并极大的减少了传统的在频域中进行相位校准一直存在的测量次数过多,效率低的问题。本发明通过在时域利用随机扰动和迭代校准时延从而实现天线阵列各单元同步接收的方法,弥补了在时域实现宽带天线阵列校准的空白,并且改善了目前天线阵列在频域校准方法当中测量次数过多的问题,极大的提高了对宽带天线阵列进行校准的效率。(The invention discloses a method for calibrating a broadband antenna array in a time domain, which comprises the steps of calibrating the antenna array in the time domain, determining a time delay range according to the number of antennas, applying a simultaneous disturbance random estimation (SPSA) algorithm and respectively using P to calculate the time delay range in And P k Difference of difference P in Ratio of (1) to (R) k The target time delay is obtained through optimization as a loss function, the algorithm can be directly applied to the calibration of the broadband antenna array, and the problems of excessive measurement times and low efficiency existing in the conventional phase calibration in the frequency domain are greatly reduced. The method for realizing synchronous receiving of the antenna array units by utilizing random disturbance and iterative calibration time delay in the time domain makes up for the blank of realizing broadband antenna array calibration in the time domain, solves the problem of excessive measurement times of the conventional antenna array in the frequency domain calibration method, and greatly improves the efficiency of calibrating the broadband antenna array.)

1. A method for calibrating a broadband antenna array in the time domain is characterized in that the method is directly calibrated in the time domain and can be applied to large-scale arrays, and comprises the following steps:

step 1, determining a range of time t and an input source signal s (t);

step 2, determining the time delay of each antenna according to the number of the antennas, namely when the number of the antennas is N, the instantaneous time delay vector of each antenna can be represented as T_inAnd the maximum delay range of each channel is [ -0.01 XN, 0.01 XN]；

Step 3, determining the instantaneous time delay vector T_inAnd the predicted delay vector T_kWhere the number of iterations k is 0;

step 4, receiving the source signal transmitted in the far field of the array through an actual antenna array system, and outputting an instantaneous signal S by the receiving system_inMeasuring instantaneous signal power P_in；

Step 5, inputting a source signal in a virtual receiving system constructed in the algorithm to generate a pre-estimated time delay vector T_kRepresenting the estimated time delay of each antenna, and outputting an estimated signal S synthesized according to the estimated time delay_kMeasuring the estimated signal power P_k；

Step 6, respectively using P_inAnd P_kDifference of difference P_inRatio of (1) to (R)_kAs a function of loss, where R_kIs S_inAnd S_kThe correlation coefficient of (a); optimizing time delay by using a simultaneous disturbance random estimation algorithm, and obtaining a pre-estimated signal S meeting a convergence condition through k times of iteration_kAt this time, the corresponding estimated delay vector T_kCan be used to calibrate the instantaneous delay vector T_in。

2. The method as claimed in claim 1, wherein the step 6 is performed by using P as the reference value_inAnd P_kDifference of difference P_inThe specific steps of using the simultaneous disturbance random estimation algorithm to optimize the time delay are as follows:

s1 as P_inAnd P_kDifference of difference P_inRatio of (A to B)Determining the parameter ap as a loss function_k,cp_k(ii) a Wherein P is_inFor instantaneous signal power, P_kEstimating the signal power;

s2, whenWhen the temperature of the water is higher than the set temperature,

T_k+1＝T_k-ap_kgp_k (2)

k＝k+1 (3)

wherein gp is_kIs the gradient vector produced by the perturbation; delta_kIs an M-dimensional vector, where M is the number of antenna elements in the array, whose elements are +1, -1, and which conforms to a bernoulli distribution with a probability of 0.5;

s3, judgmentIf true, recording T at the moment_k(ii) a Otherwise, the process returns to step S2.

3. The method of claim 2, wherein the ap is used for calibrating the wideband antenna array in the time domain_k,cp_kIs to ensure the gradient vector gp_kNo diffusion, ap, with increasing number of iterations_kLess than 0.01P_in，cp_kLess than 0.001P_in。

4. The method for time-domain calibration of a wideband antenna array as claimed in claim 1, wherein the step 6 is performed at 1-R_kThe specific steps of using the simultaneous disturbance random estimation algorithm to optimize the time delay as a loss function are as follows:

p1, note S_inAnd S_kHas a function correlation coefficient of R_kIs prepared by mixing L_r＝1-R_kDetermining the parameter ar as a loss function_k,cr_k，

Wherein, Cov (S)_in,S_k) Is S_inAnd S_kOf (a) covariance, Var [ S ]_in]Is S_inVariance of (1), Var [ S ]_k]Is S_kThe variance of (a);

p2, when L_r＝1-R_kWhen the content of the organic acid is more than or equal to 0.01,

T_k+1＝T_k-ar_kgr_k (6)

k＝k+1 (7)

wherein, gr_kRepresenting a gradient vector generated by the perturbation; delta_kIs an M-dimensional vector, where M is the number of antenna elements in the array, whose elements are +1, -1, and which conforms to a bernoulli distribution with a probability of 0.5;

p3, judgment L_r＝1-R_k<If 0.01 is true, if yes, recording T at the moment_k(ii) a Otherwise, the procedure returns to step P2.

5. The method as claimed in claim 4, wherein the ar is a linear function of the time domain of the wideband antenna array_k,cr_kIs taken to ensure gr_kNo diffusion, cr, with increasing number of iterations_k＝0.01，ar_kThe following were used:

Technical Field

The invention relates to a method for calibrating a broadband antenna array in a time domain, belonging to the field of microwave engineering and automatic control.

Background

The aperture array has wide application prospect and advantages in the fields of microwave engineering and technology. High signal-to-noise ratio can be obtained even without any mechanical operation, while suppressing directional interference and realizing multi-beam scanning. However, precise pointing of the phased array antenna beam requires precise control of the phase and amplitude of each element, requiring a large number of array antennas to achieve maximum array performance. Therefore, the phase calibration of the array antenna is significant to the application of the aperture array. Most of the existing calibration methods perform phase calibration in the frequency domain. The number of measurements required for these methods can be quite large. The time domain phase calibration method provided by the scheme can effectively reduce the measurement times in the calibration process. In the calibration process, a Simultaneous disturbance Stochastic estimation (SPSA) algorithm is used, and the algorithm is an effective method for realizing multi-parameter optimization. In the implementation process of the algorithm, the gradient problem of the general optimization algorithm is solved. The scheme realizes the calibration of the broadband antenna array in the time domain by applying the algorithm.

Disclosure of Invention

The purpose of the invention is as follows: the invention provides a method for calibrating a broadband antenna array in a time domain, and an assumed source signal is a short pulse working in the time domain. The invention applies a simultaneous disturbance random estimation (SPSA) optimization algorithm, respectively using P_inAnd P_kDifference of difference P_inRatio of (1) to (R)_kThe target time delay is obtained through optimization as a loss function, the algorithm can be directly applied to the calibration of the broadband antenna array, and the problems of excessive measurement times and low efficiency existing in the conventional phase calibration in the frequency domain are greatly reduced.

The technical scheme is as follows: a method for calibrating a broadband antenna array in the time domain includes an antenna arrayCalibrating in a time domain, and optimizing by using a simultaneous disturbance random estimation (SPSA) algorithm according to a time delay range determined by the number of the antennas so as to obtain corresponding time delay of each antenna; in the algorithm, P is respectively used_inAnd P_kDifference of difference P_inRatio of (1) to (R)_kAs a function of the loss. The method specifically comprises the following steps:

step 1, determining a range of time t and an input source signal s (t);

step 2, determining the time delay of each antenna according to the number of the antennas, namely when the number of the antennas is N, the instantaneous time delay vector of each antenna can be represented as T_inAnd the maximum delay range of each channel is [ -0.01 XN, 0.01 XN]；

Step 3, determining the instantaneous time delay vector T_inAnd the predicted delay vector T_kWhere the number of iterations k is 0;

step 4, receiving the source signal transmitted in the far field of the array through an actual antenna array system, and outputting an instantaneous signal S by the receiving system_inMeasuring instantaneous signal power P_in；

Step 5, inputting a source signal in a virtual receiving system constructed in the algorithm to generate a pre-estimated time delay vector T_kRepresenting the estimated time delay of each antenna, and outputting an estimated signal S synthesized according to the estimated time delay_kMeasuring the estimated signal power P_k；

Step 6, respectively using P_inAnd P_kDifference of difference P_inRatio of (1) to (R)_kAs a function of loss, where R_kIs S_inAnd S_kThe correlation coefficient of (a); optimizing time delay by using a simultaneous disturbance random estimation algorithm, and obtaining a pre-estimated signal S meeting a convergence condition through k times of iteration_kAt this time, the corresponding estimated delay vector T_kCan be used to calibrate the instantaneous delay vector T_in。

Further, the step 6 is performed by P_inAnd P_kDifference of difference P_inThe specific steps of using the simultaneous disturbance random estimation algorithm to optimize the time delay are as follows:

s1 as P_inAnd P_kDifference of difference P_inRatio of (A to B)Determining the parameter ap as a loss function_k,cp_k(ii) a Wherein P is_inFor instantaneous signal power, P_kEstimating the signal power;

s2, whenWhen the temperature of the water is higher than the set temperature,

T_k+1＝T_k-ap_kgp_k (2)

k＝k+1 (3)

wherein gp is_kIs the gradient vector produced by the perturbation; delta_kIs an M-dimensional vector, where M is the number of antenna elements in the array, whose elements are +1, -1, and which conforms to a bernoulli distribution with a probability of 0.5;

s3, judgmentIf true, recording T at the moment_k(ii) a Otherwise, the process returns to step S2.

Further, the ap_k,cp_kTo ensure the gradient vector gp_kNo diffusion with increasing number of iterations, recommended value ap_kLess than 0.01P_inRecommendation value cp_kLess than 0.001P_in。

Further, 1-R is used in the step 6_kThe specific steps of using the simultaneous disturbance random estimation algorithm to optimize the time delay as a loss function are as follows:

p1, note S_inAnd S_kHas a function correlation coefficient of R_kIs prepared by mixing L_r＝1-R_kDetermining the parameter ar as a loss function_k,cr_k，

Wherein, Cov (S)_in,S_k) Is S_inAnd S_kOf (a) covariance, Var [ S ]_in]Is S_inVariance of (1), Var [ S ]_k]Is S_kThe variance of (a);

p2, when L_r＝1-R_kWhen the content of the organic acid is more than or equal to 0.01,

T_k+1＝T_k-ar_kgr_k (6)

k＝k+1 (7)

wherein, gr_kRepresenting a gradient vector generated by the perturbation; delta_kIs an M-dimensional vector, where M is the number of antenna elements in the array, whose elements are +1, -1, and which conforms to a bernoulli distribution with a probability of 0.5;

p3, judgment L_r＝1-R_k<If 0.01 is true, if so, recording T at that time_k(ii) a Otherwise, the procedure returns to step P2.

Further, said ar_k,cr_kThe guaranteed gradient vector gr_kNo diffusion with increasing number of iterations, recommended value cr_k＝0.01，ar_kThe following were used:

has the advantages that:

the invention provides a method for calibrating a broadband antenna array in a time domain, which directly uses short pulse broadband signals in the time domain, applies an SPSA algorithm and respectively uses P to calibrate the broadband antenna array in the time domain_inAnd P_kDifference of difference P_inRatio of (1) to (R)_kDisturbing each channel as a loss function at the same time, and obtaining the corresponding time delay of each antenna by iterating until the convergence condition is met, thereby realizing the time domain of the phased arrayAnd (6) calibrating. The conventional antenna array is calibrated in a frequency domain, the method creatively provides that the calibration is directly carried out in a time domain, the condition that the measurement and calculation times are excessive in the past calibration is improved, the efficiency of realizing the calibration of the array antenna is greatly improved, and the method provides guarantee for the application of the ultra-wideband phased array antenna, particularly a large-scale array.

Drawings

FIG. 1 shows an ideal output signal and a source signal received by an actual antenna array system, and an instantaneous signal S output by the receiving system_inThe number of antennas is 10 at this time.

FIG. 2 shows an instantaneous signal and an estimated signal after time domain calibration.

FIG. 3 shows the loss function as P_inAnd P_kDifference of difference P_inThe ratio of the number of antennas to the number of iterations k and T of the algorithm_inAnd T_kGraph of standard deviation of (d).

FIG. 4 shows the loss function as 1-R_kThe number of antennas and the number of iterations k and T_inAnd T_kGraph of standard deviation of (d).

Fig. 5 is a graph showing the relationship between the number of iterations k and the convergence rate of the loss function in the case of two types of loss functions.

FIG. 6 is a flow chart of the algorithm of the present invention.

Detailed Description

The invention will be further described with reference to the accompanying drawings in which:

in this embodiment, a phased array antenna with an antenna number N of 1000 is taken as an example, and an antenna array instantaneous delay vector is T_inThe instantaneous signal being S_inMeasuring the instantaneous signal power to be P_in. Generating an initial predicted delay vector T₀Range and T_inThe same is true.

With P_inAnd P_kDifference of difference P_inThe ratio is used as a loss function, the SPSA algorithm is used for optimizing time delay, and a pre-estimated signal S meeting the convergence condition is obtained through k times of iteration_kAt this time, the corresponding estimated delay vector T_kCan be used for calibrating the time delay vector T_in。

Will S_inAnd S_kIs denoted as R_k1-R_kFor a loss function, the time delay is optimized by using an SPSA algorithm, and a pre-estimated signal S meeting a convergence condition is obtained through k times of iteration_kAt this time, the corresponding estimated delay vector T_kCan be used for calibrating the time delay vector T_in。

A method for calibrating a wideband antenna array in the time domain, as shown in fig. 6, includes the following steps:

step 1, determining a time range t;

-15ns≤t≤15ns (1)

step 2, determining an input source signal s (t), wherein the source signal s (t) used by the invention is as follows:

step 3, determining T according to the number N of the antennas in the phased array_inAnd T_kE.g. when the number of antennas N is 1000, T_inAnd T_kA range of (d);

-0.01N≤T_in,T₀≤0.01N (3)

T_in＝[T_in,1 T_in,2 … T_in,m … T_in,N] (4)

T_k＝[T_k,1 T_k,2 … T_k,m … T_k,N] (5)

step 4, determining an initial output signal S_inAnd measuring its power P_in；

P_in＝E{|S_in(t)|²} (7)

Step 5, determining the loss function, and the parameter ap_k,cp_k

ap_k＝0.01 (9)

cp_k＝0.001 (10)

Step 6, whenWhen the temperature of the water is higher than the set temperature,

T_k+1＝T_k-ap_kgp_k (12)

k＝k+1 (13)

wherein, Δ_kIs an M-dimensional vector, where M is the number of antenna elements in the array, whose elements are +1, or-1, and conforms to a bernoulli distribution with a probability of 0.5;

step 7, judgmentIf true, recording T at the moment_kOtherwise, returning to the step 6.

Step 8, determining the loss function, and the parameter ar_k,cr_k

L_r＝1-R_k (14)

cr_k＝0.01 (16)

Wherein, Cov (S)_in,S_k) Is S_inAnd S_kOf (a) covariance, Var [ S ]_in]Is S_inVariance of (1), Var [ S ]_k]Is S_kThe variance of (a);

step 9, when L is_r＝1-R_kWhen the content of the organic acid is more than or equal to 0.01,

T_k+1＝T_k-ar_kgr_k (19)

k＝k+1 (20)

wherein, Δ_kIs an M-dimensional vector, where M is the number of antenna elements in the array, whose elements are +1, or-1, and conforms to a bernoulli distribution with a probability of 0.5;

step 10, judging L_r＝1-R_k<If 0.01 is true, if so, recording T at that time_kOtherwise, the step 9 is returned.