A method for measuring millimeter wave antenna pointing error using a spread source

Abstract

The application provides a method for measuring millimeter wave antenna pointing error by using a spread source, comprising the following steps: scanning a selected calibration source by using a millimeter wave antenna of a telescope, and recording calibration data obtained from the spread source; and processing the calibration data from the spread source by using a deconvolution algorithm, and obtaining the pointing error angle of the current azimuth axis and the current elevation axis according to the deconvolution result. The method for measuring millimeter wave antenna pointing error by using a spread source effectively solves the problem of insufficient accuracy in the pointing calibration of the existing millimeter wave radio telescope by using the deconvolution algorithm and the noise suppression technology, significantly improves the calibration accuracy of the radio telescope, and promotes the progress of high-frequency radio astronomy observation.

Description

Technical Field

[0001] The invention belongs to the field of radio astronomy and relates to a method for measuring the pointing error of a millimeter wave antenna by utilizing a spread source. Background Art

[0002] Existing radio telescope pointing calibration techniques primarily include the cross calibration method and the five-point calibration method. These techniques have been widely used in astronomical observations to ensure telescope pointing accuracy and data quality. They detect and correct deviations between the telescope's actual pointing position and its theoretical position by scanning known celestial objects or signal sources. However, with the increasing frequency of radio telescope observations, especially in high-frequency bands (such as the W band), existing techniques have shown some limitations and shortcomings in their application.

[0003] The cross calibration method determines pointing deviation by scanning the radio telescope in both the horizontal and vertical directions and detecting the maximum signal intensity. Although this method is simple to operate, requires few steps, and is suitable for quickly estimating errors, its accuracy is limited in some scenarios. This is especially true when observing fainter celestial bodies, where signal intensity fluctuations are small, resulting in insufficient accuracy in the calculated error. Furthermore, when the telescope's initial pointing error is large, the cross calibration method may not be accurate enough, making it ineffective for observations requiring high precision.

[0004] The five-point calibration method provides a more accurate estimation of pointing error than the cross calibration method by measuring at five different points around the target celestial body. This method performs well in high-precision scenarios, but its operation is complex, the measurement time is long, and it requires analysis of multiple measurement data, which increases the time and resource costs in use. In addition, the five-point method is mainly suitable for point source calibration. When extended sources (such as the sun, moon, etc.) are required for calibration, the existing five-point method shows obvious shortcomings. Due to the small change in signal intensity between the center point and the edge point, the five-point calibration method is difficult to accurately identify the telescope pointing error.

[0005] As radio telescope observation frequencies increase, especially in the W-band and higher, new challenges arise in radio telescope design. High-frequency observations require extremely high surface accuracy, as higher frequencies correspond to shorter wavelengths, and any slight surface error significantly impacts observation accuracy. However, to meet this surface accuracy requirement, the telescope aperture cannot be designed to be very large. This limitation directly results in a smaller effective antenna aperture, which reduces the system equivalent flux density (SEFD). In other words, the telescope's sensitivity is limited, making it more difficult to effectively capture weak radio signals.

[0006] In addition, as the frequency increases, the radio radiation of celestial bodies (such as blackbody radiation or thermal radiation) decreases significantly. This makes the radio sources even weaker in the high-frequency band. Due to the small antenna aperture and low SEFD, traditional point source calibration targets (such as compact galaxies, active galactic nuclei or quasars) are difficult to meet the pointing calibration requirements of high-frequency telescopes. Therefore, in these frequency bands, calibration sources are often selected from extended sources with large viewing angles such as the sun and the moon. However, the existing cross calibration method and five-point calibration method are mainly designed for point sources, and are not effective for these extended sources.

[0007] Specifically, when using a spread source for pointing calibration, the cross-calibration method typically produces a convolution of the celestial object's outline and the antenna's aperture field, rather than the antenna's true beam pattern. This convolution effect significantly reduces calibration accuracy. The five-point calibration method is even more problematic when using a spread source. Because the signal strength in the center of the spread source varies little, measurement errors can become ambiguous, and the center point's angle can fluctuate by as much as 0.5 degrees, affecting calibration accuracy.

[0008] In summary, as observation frequencies increase, traditional pointing calibration methods, such as the cross calibration method and the five-point calibration method, face the following technical challenges: First, the radiation intensity of commonly used point sources (such as extragalactic radio sources) decreases significantly at high frequencies, failing to provide sufficient signal strength, making them unsuitable for accurate pointing calibration. Therefore, observations often rely on calibration using extended sources (such as the Sun and Moon). Second, as the frequency of radio telescopes increases, the accuracy requirements for the panels increase significantly. For radio telescopes observing in millimeter-wave and higher frequency bands (such as the W-band), the precision requirements for the telescope panels are extremely high, limiting the aperture size and, in turn, the system equivalent flux density (SEFD). This makes it difficult to achieve high-precision results using traditional pointing calibration methods. Finally, traditional cross calibration and five-point calibration methods have significant limitations when dealing with extended sources. Traditional methods use point sources to measure calibration errors, but when using extended sources, the convolution effect between the extended source profile and the antenna aperture field results in low calibration accuracy. Due to the lack of a spread source processing algorithm, the traditional cross calibration method cannot effectively distinguish the influence of the celestial body contour because the measured deviation angle is not able to effectively distinguish the influence of the spread source contour, so that the measured pointing error is affected by the spread source contour, resulting in the inability to obtain the true antenna beam pattern, thus affecting the accuracy of the pointing calibration.

[0009] Therefore, the existing cross-calibration method and five-point calibration method have significant limitations in high-frequency bands and extended source calibration, and cannot meet the current needs of high-precision observations. This urgently requires the development of high-precision calibration technology that can handle extended sources to address the shortcomings of existing technologies and improve the calibration capabilities of radio telescopes. Summary of the Invention

[0010] The object of the present invention is to provide a method for measuring the pointing error of a millimeter wave antenna by using an extended source, so as to improve the accuracy of pointing calibration by using an extended source and avoid the pointing error being affected by the extended source profile.

[0011] To achieve the above object, the present invention provides a method for measuring the pointing error of a millimeter wave antenna using a spread source, comprising:

[0012] S1: Scan the selected calibration source using the millimeter wave antenna of the telescope and record the calibration data, where the calibration source is a spread source;

[0013] S2: Process the calibration data from the spread source through the deconvolution algorithm, and obtain the current pointing error angles of the azimuth axis and pitch axis according to the deconvolution result.

[0014] In step S1 , the scanning method used for scanning includes one of a cross scanning method, a butterfly scanning method, and an OTF imaging scanning method.

[0015] The scanning method used for scanning is a cross scanning method; the step S1 specifically includes:

[0016] S11: Input several control parameters;

[0017] S12: driving the millimeter wave antenna to track the spread source to ensure that the millimeter wave antenna points to the center of the spread source;

[0018] S13: Perform scanning, and record calibration data used to determine the pointing error of the antenna in real time during the scanning process.

[0019] During scanning, the scanning range includes a high-speed scanning area and a low-speed scanning area. The high-speed scanning area corresponds to the scanning area deviating from the spread source, and the low-speed scanning area corresponds to the scanning area pointing to the spread source or near the spread source.

[0020] The step S2 specifically includes:

[0021] S21: preprocessing the calibration data;

[0022] S22: Introduce the spread source model and discretize the spread source brightness value to distribute in the azimuth angle offset δ AZ On the grid, it is recorded as the discrete value H(θ) of the source brightness;

[0023] S24: converting the preprocessed data from the time domain to the frequency domain using a fast Fourier transform to obtain a frequency domain scanning result Y(θ);

[0024] S25: performing a deconvolution operation based on the frequency domain scanning result Y(θ) and the discrete value H(θ) of the spread source brightness to obtain an ideal signal X(θ) after deconvolution processing;

[0025] S26: performing smoothing filtering on the ideal signal X(θ) after the deconvolution processing to obtain a filtered ideal signal X'(θ);

[0026] S27: Perform inverse Fourier transform on the filtered ideal signal X'(θ) to restore it to the time domain and obtain the deconvolution result X(t);

[0027] S28: Perform Gaussian model fitting on the deconvolution result X(t) to obtain the mean of the Gaussian model as the pointing error angle of the azimuth axis and the pitch axis.

[0028] The calibration data includes the azimuth angle θ of the antenna AZ , pitch angle θ EL , azimuth angle offset δ AZ , pitch angle offset δ EL , signal strength P and millisecond timestamp;

[0029] In step S21, the calibration data is pre-processed, specifically including: the azimuth angle θ of all scanning ranges AZ , pitch angle θ EL , azimuth angle offset δ AZ , pitch angle offset δ EL Grid processing is performed to obtain preprocessed data, and the signal strength P is normalized.

[0030] In step S22, the brightness value of the source is discretized and distributed in the azimuth angle offset δ AZ When the grid is on the same grid, it also includes the azimuth angle offset δ AZ The zero point is defined as the geometric center of the source.

[0031] After step S22 and before step S24, the method further includes step S23: estimating noise using the pre-processed data of the scanning area deviating from the spread source, and subtracting the noise to obtain pre-processed data of the low-speed scanning area after noise subtraction;

[0032] The step S23 specifically includes:

[0033] S231: For the pre-processed data of the pitch angle, remove the signal strength data P(θ) of the scanning area that deviates from the spread source during the scanning process and use it as noise data;

[0034] S232: Perform linear fitting on the signal intensity data P(θ) of the scanning area that deviates from the spread source, and the fitting result is the signal intensity y(θ) of the noise. Then, the signal intensity y(θ) of the noise is deducted from the signal intensity P(θ) of the low-speed scanning area to obtain the signal intensity P'(θ) of the low-speed scanning area after noise deduction.

[0035] In step S25, the ideal signal X(θ) after deconvolution is:

[0036]

[0037] Among them, X(θ) is the ideal signal after deconvolution processing, Y(θ) is the frequency domain scanning result, is the transfer function of the solar model, which is the FFT transform result of the discrete value H(θ) of the source brightness.

[0038] This method, using an extended source to measure millimeter-wave antenna pointing errors, addresses technical challenges in millimeter-wave radio telescope pointing calibration, particularly when using extended sources (such as the Sun or Moon) for high-frequency observations, where traditional calibration methods lack sufficient accuracy. By processing extended source data using a deconvolution algorithm, this method accurately measures the antenna's azimuth and elevation errors, significantly improving the accuracy of pointing calibration.

[0039] Improved calibration accuracy: Experiments have shown that this method, through the deconvolution algorithm, can improve the measurement accuracy of pointing error angles to sub-radian levels, significantly exceeding traditional cross-calibration and five-point calibration methods. This is crucial for observations in the millimeter-wave frequency band and above, and is particularly important for the pointing calibration of radio telescopes with smaller antenna apertures and low SEFD, providing greater accuracy and reliability.

[0040] Effectiveness of extended source calibration: Compared to traditional methods that rely solely on point sources for calibration, this method utilizes a deconvolution algorithm to measure pointing errors using extended sources, effectively utilizing extended sources such as the Sun and Moon for high-precision pointing calibration. This broadens the range of available calibration sources, making it particularly effective for high-frequency radio telescope observations where extragalactic radio sources are insufficient. High-performance calibration can still be achieved using strong extended sources such as the Sun.

[0041] Economic and social benefits: In practical applications, this invention can reduce observation errors caused by inaccurate calibration, thereby improving the observation efficiency of radio telescopes and reducing observation costs. Furthermore, this technology can be applied to millimeter-wave radio telescopes worldwide, promoting technological advances in astronomical observations. It has particular application value in areas such as high-frequency cosmic microwave background radiation and planetary exploration.

[0042] In addition, the present invention designs an antenna acceleration scanning strategy for a method of measuring the pointing error of a millimeter-wave antenna using a spread source, which reduces the time consumed for antenna scanning while ensuring the accuracy of the scanning data.

[0043] In summary, the method of measuring the pointing error of millimeter-wave antennas using a spread source in the present invention effectively solves the problem of insufficient accuracy in the pointing calibration of existing millimeter-wave radio telescopes through a deconvolution algorithm and noise suppression technology, significantly improves the calibration accuracy of radio telescopes, and promotes the progress of high-frequency radio astronomy observations. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is an overall flow chart of a method for measuring millimeter wave antenna pointing error using a spread source according to the present invention.

[0045] Figure 2 It is a scanning principle diagram that performs incremental scanning along the azimuth axis and the pitch axis respectively on the basis of maintaining the continuous tracking of the antenna to the sun.

[0046] Figure 3A This is the measured data diagram of the azimuth axis scanning; Figure 3B Comparison of the antenna pattern (blue) recovered after deconvolution and the Gaussian fitting curve (red).

[0047] Figure 4A This is the measured data diagram of the pitch axis scanning; Figure 4B Comparison of the antenna pattern (blue) recovered after deconvolution and the Gaussian fitting curve (red). DETAILED DESCRIPTION

[0048] The present invention will be further described below with reference to specific examples. It should be understood that the following examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention.

[0049] The present invention's method for measuring millimeter-wave antenna pointing errors using a spread source is primarily used for pre-observation pointing calibration of millimeter-wave radio telescopes. The goal is to measure the error angles of the current azimuth and elevation axes using a spread source, such as the sun or moon. In this embodiment, the method for measuring millimeter-wave antenna pointing errors using a spread source is a further improvement on the existing cross-calibration method, and is applicable to measurement data from this method.

[0050] The pointing calibration performed by the present invention primarily involves aligning the telescope's own coordinate system (including hardware and software) with another reference coordinate system, the International Celestial Reference System (ICRS), corresponding to an astronomical reference position. This compensates for the angular error between the telescope's coordinate system and the reference coordinate system. After using the error angles obtained by the present invention to compensate for the angular error between the telescope's coordinate system and the reference coordinate system, celestial observations can be performed directly using the telescope's existing coordinate system.

[0051] like Figure 1 As shown, a method of measuring the pointing error of a millimeter wave antenna using a spread source of the present invention specifically includes:

[0052] Step S1: In the data acquisition phase, the millimeter wave antenna of the telescope is used to perform a cross scan on the selected calibration source and record the calibration data;

[0053] In other embodiments, the cross-scanning method can be replaced with other types of continuous scanning methods, such as butterfly scanning or OTF (on the fly) imaging. Although different scanning methods require different data processing methods, the deconvolution concept remains the same. For continuous scanning, the effect of the spread source can be removed, rendering it the same as a point source scan, allowing for processing using the original method.

[0054] Regardless of the scanning method used, the calibration data includes the antenna's azimuth angle, elevation angle, azimuth angle offset, elevation angle offset, signal strength, and millisecond timestamp.

[0055] The step S1 specifically includes:

[0056] Step S11: To ensure the accuracy of the scan, input several control parameters;

[0057] In this embodiment, the scanning method is a cross scanning method, wherein the scanning range includes a high-speed scanning area and a low-speed scanning area, such as Figure 2 As shown in the figure, the dotted line part is the high-speed scanning area, which actually corresponds to the scanning area away from the spread source, and the solid line part is the low-speed scanning area, which actually corresponds to the scanning area pointing to the spread source or near the spread source; the difference between the two is the speed of the scanning. The input control parameters include: pitch scanning width B EL0 , command interval t0, low-speed scan width B EL , low speed scanning speed v s 、High and low magnification k v The specific meanings of each control parameter are shown in Table 1.

[0058] That is to say, in this embodiment, the cross scanning method used is different from the existing cross scanning method. Conventional cross scanning does not have speed constraints. In this embodiment, the speed is constrained when performing cross scanning on the selected calibration source. Specifically, the low-speed scanning area inside and near the radio source is slow scanning to obtain more details; the high-speed scanning area outside the low-speed scanning width is fast scanning to quickly obtain statistical noise and the noise change trend with elevation angle during pitch axis scanning (since the noise change trend is linear, fast scanning is sufficient).

[0059] Table 1: Specific meaning of each control parameter

[0060]

[0061] Step S12: driving the millimeter wave antenna to track the spread source to ensure that the millimeter wave antenna points to the center of the spread source;

[0062] Then, prepare to scan. Since this embodiment adopts cross scanning, the detailed trajectory description is shown in Figure 2 .

[0063] Step S13: Perform scanning, and record calibration data used to determine the pointing error of the antenna in real time during the scanning process.

[0064] like Figure 2 As shown, at the beginning of the scan, the antenna is offset by a certain distance in the direction of increasing azimuth angle to obtain the positive azimuth scan result, and then offset by a certain distance in the direction of gradually decreasing azimuth angle to obtain the negative azimuth scan result. At this point, the scan covers the positive and negative azimuth contours of the target, completing the horizontal scan of the azimuth angle. Next, the antenna is offset in the direction of the elevation angle, also covering the positive and negative elevation contours of the target, completing the vertical scan and forming a "cross" shaped scanning track. The advantage of cross scanning is that it is fast. Cross scanning can be regarded as a way to control variables. The purpose is to take the error under a certain azimuth and elevation angle, and take the maximum value after a rapid scan of the azimuth; then quickly scan the pitch to take the maximum value. Figure 2 In the cross scanning method shown, AZ is the azimuth axis and EL is the elevation axis. Figure 2 The black solid line part in the middle is slow scanning, and the dotted line part is high-speed scanning. The specific speed value and slow speed range are determined by the input parameters.

[0065] In this embodiment, the calibration data used to determine the pointing error of the antenna includes the azimuth angle θ of the antenna. AZ , pitch angle θ EL , azimuth angle offset δ AZ , pitch angle offset δ EL , signal strength P and millisecond timestamp. The specific meanings of these calibration data are shown in Table 2. These calibration data will be used in subsequent data processing to determine the antenna pointing error.

[0066] Among them, the azimuth angle offset δ AZ , pitch angle offset δ ELSpecifically, it is determined in the following way: Since the software controls the antenna, the present application knows the current angle and the command angle (the instruction value from the computer) based on the received signal and the recorded signal of the servo motor. In addition, the current target angle can be calculated based on the known time. Among them, the antenna is controlled to rotate by the servo system, and the command angle currently executed by the antenna received by the servo system is the command angle. In addition, the current angle of the antenna monitored by the code disk is also transmitted to the servo system, so the angle at which the antenna is currently pointing, recorded by the servo system, is the current angle. In other words, the command angle and the current angle are both based on the numerical value of the servo system. At the same time, the command angle currently executed and the angle of the current antenna provided by the servo system are the command angle and the current angle in this article. The target angle refers to the ideal azimuth position of the source, which is the geometric center of the source. Therefore, the target angle can be obtained by theoretical calculation based on astronomical ephemeris and time.

[0067] Scan source is to control the position of the antenna according to Figure 2 The direction shown is moving, but since the source is also moving, in actual engineering applications, in addition to the command angle, a deviation angle is also used. This deviation angle indicates the degree to which the antenna deviates from the source with high precision due to time delay. When controlling the antenna, after the computer issues the command angle, the servo system gradually rotates to the command angle, which results in a certain amount of time delay. Therefore, to avoid errors caused by this delay, the computer typically discretizes the deviation angle and periodically sends it as the deviation angle. This ensures that the commands are sent and completed in sequence. The servo system then records the current angle observed by the entire scanning process, the currently executed command angle, and the millisecond timestamp. The antenna's desired position is then calculated based on the time and the celestial object's orbit / coordinates. The difference between the antenna's current desired position and its current angle (i.e., the actual angle at which the antenna is pointing) is the actual angle deviation at that moment. Furthermore, all devices used in telescope control are synchronized by a time server, which is why this method can avoid time delays.

[0068] Therefore, the angle offset satisfies the following equation: Angle offset = Command angle + Deviation angle - Target angle. (The Command angle + Deviation angle can be considered the actual angle at which the antenna is pointing, while the Target angle is the position at which the antenna should currently be pointing.)

[0069] Table 2: Meaning of calibration data

[0070]

[0071] It should be noted that the azimuth angle θ here is AZ and pitch angle θ EL are the current angles of the antennas mentioned above.

[0072] Step S2: data processing stage, i.e. processing the calibration data from the source by deconvolution algorithm to eliminate the influence of the celestial body profile, and obtaining the current pointing error angle of the azimuth axis and the elevation axis according to the deconvolution result.

[0073] In the embodiment, the sun is taken as an example of the source.

[0074] The step S2 specifically comprises:

[0075] Step S21: pre-processing the calibration data to facilitate subsequent data processing.

[0076] In the embodiment, the calibration data is pre-processed, specifically comprising: performing grid processing on the azimuth angle θ AZ , the elevation angle θ EL , the azimuth angle offset δ AZ , and the elevation angle offset δ EL of all scanning ranges to obtain pre-processed data (including angle offset θ -Signal intensity P(θ)) and performing normalization processing on the signal intensity P.

[0077] Wherein, the angle accuracy of the grid processing is t0×v s . In the embodiment, the data of the cross-scan includes AZ+, AZ-, EL+, and EL- four parts, and here, the AZ+ is taken as an example, the azimuth angle θ AZ , the elevation angle θ EL , the azimuth angle offset δ AZ , and the elevation angle offset δ EL of all scanning ranges are performed grid processing, specifically comprising:

[0078] Step S211: taking the azimuth angle θ AZ , the elevation angle θ EL , and the signal intensity P collected over time as dependent variables, and taking the azimuth angle offset δ AZ as independent variable, the grid data is integrated by using linear interpolation method.

[0079] In the interpolation, only the azimuth angle offset δ AZ is the independent variable, and the others are dependent variables changing with the azimuth angle offset δ AZ . After the interpolation, the interval of the azimuth angle offset δ AZ between adjacent grid points is t0×v s .

[0080] Therefore, after the grid processing, the multi-dimensional data with the discrete data of the offset angle uniform step as independent variable can be obtained, wherein each grid point represents an azimuth angle offset δ AZand the corresponding signal strength, the azimuth angle, the elevation angle.

[0081] The normalization formula of the signal strength P uses the conventional formula of normalization using the maximum value and the minimum value.

[0082] The angle offset θ is the azimuth angle θ AZ or the elevation angle θ EL .

[0083] Step S22: Introduce the source model, and discretely distribute the source brightness value on the grid of the azimuth angle offset δ AZ , denoted as the discrete value H(θ) of the source brightness;

[0084] Therefore, the subsequent processing will be based on the center position of the source to exclude the error caused by the position deviation.

[0085] The source model specifically includes the intensity distribution of the brightness of the source in the reference coordinate system, and when discretely distributing the source brightness value on the grid of the azimuth angle offset δ AZ , it also includes defining the zero point of the azimuth angle offset δ AZ as the geometric center of the source. Since the time is known, the position of the geometric center of the source (i.e., the target angle) is also known. Therefore, the change in brightness that changes from the position of the geometric center is the source model of the present application. The specific physical unit of the source brightness value can be temperature (Kelvin) or power (mW), as long as it is a linear unit, not a dB type unit, because the calibration does not care about the absolute intensity.

[0086] In the present embodiment, the source is the sun, so the source model is the sun model, and the input sun model is the intensity distribution of the brightness of the sun.

[0087] The sun model can use private observation data (such as observed discrete value-offset angle model data of the brightness of the sun) or directly use a square wave instead. In the present embodiment, the azimuth angle offset δ AZ can be directly used as an input parameter to substitute into the sun model to obtain the corresponding sun brightness value, or the observation data of the sun model can be used as a basis to align the data granularity of the grid of the azimuth angle offset δ AZ through interpolation, and then obtain the discrete distribution of the sun brightness value.

[0088] Next, we reduce the influence of noise on deconvolution through mean filtering.

[0089] Step S23: Estimate the noise using the preprocessed data of the scanning area deviated from the source, and subtract the noise to obtain the preprocessed data of the low-speed scanning area after noise subtraction;

[0090] In this embodiment, since the scanning speed is differentiated, the scanning area deviating from the spread source actually refers to the high-speed scanning area.

[0091] Step S23 specifically includes:

[0092] Step S231: For the pre-processed data of the pitch angle, remove the signal strength data P(θ) of the high-speed scanning area during the scanning process to serve as noise data;

[0093] Step S232: Perform a linear fit on the signal strength data P(θ) in the high-speed scanning area (i.e., using the formula y(θ) = kθ + b). The fitting result is the noise signal strength y(θ). The noise signal strength y(θ) is then subtracted from the signal strength P(θ) in the low-speed scanning area to obtain the noise-subtracted signal strength P'(θ) in the low-speed scanning area. This eliminates the influence of ambient noise during pitch scanning.

[0094] During elevation scanning, changes in elevation angle have a significant impact on ambient noise. However, during azimuth scanning, changes in elevation angle are minimal. Changes in the elevation axis cause noise changes, while changes in the elevation axis are negligible for azimuth scanning. Therefore, it is necessary to specifically subtract ambient noise from the preprocessed data for elevation scanning. This step is skipped for preprocessed data for azimuth angles.

[0095] The fitting parameters obtained by the formula y(θ) = kθ + b include k and b, and the angle of the low-speed part is taken as θ. The pre-processed data of the low-speed scanning area after noise subtraction includes:

[0096] The signal intensity P'(θ) of the low-speed scanning area after noise subtraction = the signal intensity P(θ) of the low-speed scanning area - the signal intensity y(θ) of the noise.

[0097] Step S24: using a fast Fourier transform (FFT) to convert the pre-processed data (angle offset θ-signal strength P(θ)) from the time domain (or spatial domain) to the frequency domain to obtain a frequency domain scanning result Y(θ);

[0098] The Fast Fourier Transform (FFT) data processing method is the same for all scan areas. The preprocessed data (angle offset θ - signal strength P(θ)) includes signal strength, offset angle, corresponding current elevation angle, current azimuth angle, and time. It is a sequence of time slices, allowing the preprocessed data to be transformed into the frequency domain.

[0099] The frequency domain scanning result Y(θ) is a frequency domain representation of the observation data after noise subtraction. The independent variable of the frequency domain scanning result Y(θ) is the angle offset θ, and the dependent variable is the frequency domain representation of the signal intensity. Thus, in the frequency domain, the convolution operation is converted into multiplication, thereby making the subsequent deconvolution operation more convenient.

[0100] Step S25: Based on the frequency domain scanning result Y(θ) and the discrete value H(θ) of the extended source brightness, a deconvolution operation is performed to obtain an ideal signal X(θ) after deconvolution processing.

[0101] According to the deconvolution theorem, the ideal signal X(θ) after deconvolution processing is:

[0102]

[0103] where X(θ) is the ideal signal after deconvolution processing, Y(θ) is the frequency domain scanning result, is the transfer function of the sun model, which is the FFT transform result of the discrete value H(θ) of the extended source brightness.

[0104] Deconvolution is a core step, which is used to remove the signal spreading effect caused by the extended source (sun) from the measurement data. By using the previously obtained extended source model as the convolution kernel, the convolution effect can be reversed to restore the point spread function of the radio telescope.

[0105] Step S26: The ideal signal X(θ) after deconvolution processing is subjected to a smoothing filter processing to obtain a filtered ideal signal X'(θ).

[0106] As can be seen from the deconvolution formula, when there is a small value (noise) in H(θ), the noise may be amplified. Therefore, we need to perform smoothing filter processing on the real part and the imaginary part of the ideal signal X(θ) after deconvolution processing in the frequency domain, respectively.

[0107] Since the beam width of the actual point spread function should be close to the theoretical beam width of the antenna, in step S26, when performing the smoothing filter processing, the filter window is set to be a common factor smaller than the theoretical beam width of the antenna. The theoretical beam width of the antenna usually refers to the HPBW (half power beam width, HPBW, half power beam width), which is calculated as: HPBW = 1.02 * observed wavelength / aperture.

[0108] Furthermore, since the sampling rate of the data item signal strength is limited, the antenna offset angle corresponding to the sampling interval is the lower limit of the filter window. If the filter window exceeds the antenna offset angle corresponding to the sampling interval by a large margin, the data itself will exhibit excessive interpolation characteristics. Therefore, in step S26, when performing the smoothing filter process, the filter window is also set to be larger than the antenna offset angle corresponding to the actual sampling interval. In other words, it is recommended that the filter window size satisfy the requirement that the theoretical antenna beamwidth > window > measured data sampling interval.

[0109] Step S27: Perform inverse Fourier transform on the filtered ideal signal X'(θ) to restore it to the time domain to obtain a deconvolution result X(t).

[0110] The deconvolution result X(t) includes the azimuth angle offset δ AZ and the pitch angle offset δ EL The corresponding signal strength data has the angle offset as the independent variable and the signal strength as the dependent variable. At this time, the signal strength data corresponding to the angle offset has eliminated the convolution effect of the spread source profile and can more accurately reflect the actual pointing error of the antenna.

[0111] Step S28: performing Gaussian model fitting on the deconvolution result X(t) to obtain the mean of the Gaussian model as the pointing error angle of the azimuth axis and the pitch axis.

[0112] The Gaussian model formula is as follows:

[0113]

[0114] Here, A is the amplitude (peak value) of the function, μ is the mean (center position), σ is the standard deviation (determines the width of the distribution), x is the independent variable, and f(x) is the dependent variable. Therefore, fitting yields the three parameters A, μ, and σ, and the resulting mean μ is the precise error angle.

[0115] In summary, the present invention can obtain the positive and negative error angles of azimuth and elevation through the above deconvolution operation. These error data will be used to adjust the actual pointing of the antenna to ensure that the calibration accuracy of the telescope meets the observation requirements.

[0116] Experimental results:

[0117] To research and validate millimeter-wave antenna technologies, the Shanghai Astronomical Observatory (SAO) Tianma Campus has built a 5-meter millimeter-wave radio telescope. Millimeter-wave pointing calibration is one of the most critical technologies to be researched. The 5-meter millimeter-wave radio telescope antenna system utilizes a Cassegrain antenna, a high-rigidity azimuth-elevation turntable mount, and a fully digital antenna controller. It is designed for high-quality reception of radio signals from both natural and artificial celestial bodies, covering frequencies up to the W band. The antenna subsystem primarily consists of a feed subsystem, a mechanical structure subsystem, and an antenna control subsystem.

[0118] We implemented this method on the antenna, and the measured results are shown in the following example: Figure 3A and Figure 3B (azimuth axis), Figure 4A and Figure 4B Finally, at an azimuth angle of 204.673 degrees and a pitch angle of 63.338 degrees, the azimuth axis angle deviation is -1.225 degrees, and the pitch axis deviation is -0.156 degrees.

[0119] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Various modifications are possible. Any simple, equivalent changes and modifications made in accordance with the claims and description of the present invention are within the scope of protection of the patent claims. Anything not fully described in this invention is conventional technology.

Claims

1. A method for measuring millimeter wave antenna pointing error using a spread source, characterized in that: include: Step S1: Scanning a selected calibration source using the millimeter wave antenna of the telescope to record calibration data, where the calibration source is a spread source; Step S2: Process the calibration data from the spread source using a deconvolution algorithm, and obtain the current pointing error angles of the azimuth axis and the pitch axis according to the deconvolution result; When scanning, the scanning range includes a high-speed scanning area and a low-speed scanning area. The high-speed scanning area corresponds to the scanning area deviating from the display source, and the low-speed scanning area corresponds to the scanning area pointing to the display source or near the display source. The step S2 specifically includes: Step S21: pre-processing the calibration data; Step S22: Introduce the spread source model and discretize the spread source brightness value to distribute in the azimuth angle offset On the grid, it is recorded as the discrete value of the source brightness ; Step S24: Use fast Fourier transform to convert the pre-processed data from time domain to frequency domain to obtain frequency domain scanning results ; Step S25: Based on the frequency domain scanning results and discrete values ​​of the source brightness , perform deconvolution operation to obtain the ideal signal after deconvolution processing ; Step S26: Deconvolution of the ideal signal Perform smoothing filtering to obtain the ideal filtered signal ; Step S27: Filter the ideal signal Perform inverse Fourier transform, restore to the time domain, and obtain the deconvolution result ; Step S28: Deconvolution result Perform Gaussian model fitting and obtain the mean of the Gaussian model as the pointing error angle of the azimuth axis and pitch axis; After step S22 and before step S24, the method further includes step S23: estimating noise using the pre-processed data of the scanning area deviating from the spread source, and subtracting the noise to obtain pre-processed data of the low-speed scanning area after noise subtraction; The step S23 specifically includes: Step S231: For the pre-processed data of the pitch angle, remove the signal strength data of the scanning area that deviates from the source during the scanning process. , as noise data; Step S232: Analyze the signal strength data of the scanning area away from the source. Perform linear fitting, and the fitting result is the signal intensity y of the noise , then scan the signal strength of the area at low speed The signal strength y after deducting the noise , get the signal intensity of the low-speed scanning area after noise subtraction .

2. The method for measuring the pointing error of a millimeter wave antenna using a spread source according to claim 1, wherein: In step S1 , the scanning method used for scanning includes one of a cross scanning method, a butterfly scanning method, and an OTF imaging scanning method.

3. The method for measuring the pointing error of a millimeter wave antenna using a spread source according to claim 2, wherein: The scanning method used for scanning is a cross scanning method; the step S1 specifically includes: Step S11: input several control parameters; Step S12: driving the millimeter wave antenna to track the spread source to ensure that the millimeter wave antenna points to the center of the spread source; Step S13: Perform scanning, and record calibration data used to determine the pointing error of the antenna in real time during the scanning process.

4. The method for measuring the pointing error of a millimeter wave antenna using a spread source according to claim 1, wherein: The calibration data includes the azimuth angle of the antenna , pitch angle , azimuth angle offset , pitch angle offset , signal strength P and millisecond timestamp; In step S21, the calibration data is pre-processed, specifically including: the azimuth angles of all scanning ranges , pitch angle , azimuth angle offset , pitch angle offset Grid processing is performed to obtain preprocessed data, and the signal strength P is normalized.

5. The method for measuring the pointing error of a millimeter wave antenna using a spread source according to claim 1, wherein: In the step S22, the brightness value of the source is discretized and distributed in the azimuth angle offset When the grid is on, it also includes the azimuth angle offset The zero point is defined as the geometric center of the source.

6. The method for measuring the pointing error of a millimeter wave antenna using a spread source according to claim 1, wherein: In step S25, the ideal signal after deconvolution processing is for: ， in, is the ideal signal after deconvolution processing, is the frequency domain scanning result, is the transfer function of the solar model, which is the discrete value of the source brightness The FFT transformation result of .

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