A method for automatic spurious analysis of broadband frequency converters

Abstract

The present invention proposes a method for automatic analysis of spurious signals of a broadband frequency converter, which relates to the fields of communication, radar, electronic countermeasures, microwave and radio frequency technology. The present invention obtains spurious vectors by solving a group of spurious equations, thereby achieving classification of spurious signals. The process only requires setting the relevant information of the frequency conversion relationship of the device to be tested in advance, and no manual intervention is required for the subsequent process. It can replace the traditional manual testing and analysis of spurious signals, and achieve automatic analysis of spurious signals. The classification of spurious signals by the present invention can cover indicators such as image frequency suppression, intermediate frequency suppression, harmonic suppression and spurious suppression, thereby obtaining a complete analysis result.

Description

Technical Field

[0001] The invention relates to the technical fields of communication, radar, electronic countermeasure, microwave and radio frequency, and in particular to an automatic spurious analysis method for a broadband frequency converter. Background Art

[0002] Broadband frequency converters realize signal interconnection and frequency conversion between antennas and digital terminals, and are an indispensable component of communication, radar, electronic countermeasures and integrated systems. To ensure high-performance frequency conversion, mainstream frequency converter solutions usually adopt superheterodyne technology. The inherent defects of this technology system require that the image frequency suppression, intermediate frequency suppression, harmonic suppression and spurious suppression indicators be considered during the design. For broadband frequency converters, the analysis, design, testing and debugging of these indicators are the most complex and time-consuming parts of the research and development process.

[0003] At present, the existing technology mainly focuses on how to deal with spurious signals, including: avoiding spurious signals generated by local oscillators or frequency conversion through reasonable frequency planning, adjusting the frequency conversion scheme through spurious signal testing to avoid spurious signals, and improving the impact of spurious signals caused by local oscillators or frequency converters through offset technology. However, these methods cannot achieve automatic testing and analysis of spurious signal composition. Summary of the invention

[0004] In view of this, the present invention proposes a method for automatic analysis of spurious signals of a broadband frequency converter. The method obtains spurious vectors by solving a spurious equation group, thereby achieving classification of spurious signals. The process does not require manual intervention, and automatic analysis of spurious signals can be achieved.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A broadband converter spurious automatic analysis method is applied to a spurious automatic test system; the spurious automatic test system comprises a broadband converter to be tested, a signal source, a host computer and a spectrum analyzer; wherein the operating frequency range of the broadband converter to be tested is F rfmin ~F rfmax , the sweep output frequency range of the signal source is F sweepmin ~F sweepmax The range of intermediate frequencies that can be analyzed by the spectrum analyzer is [F if ±BW if / 2],F if is the intermediate frequency, BW if is the intermediate frequency bandwidth;

[0007] The following steps are involved:

[0008] (1) Set the frequency F of the broadband inverter to be tested rf , F rf ∈F rfmin ~Frfmax ;

[0009] (2) The signal source is at F sweepmin ~F sweepmax The frequency is swept within the range, and the spectrum analyzer measures the spurious frequency F spurs and the spurious amplitude P spurs ; If the spurious amplitude P spurs Exceeding the threshold P threshold , then record the current sweep frequency F sweep , spurious frequency F spurs and the spurious amplitude P spurs , then execute steps (3) and (4); complete F sweepmin ~F sweepmax After sweeping within the range, go to step (5);

[0010] (3) Using the frequency conversion relationship of the broadband inverter to be tested, a set of spurious equations is constructed and solved to obtain a spurious vector;

[0011] (4) Analyze the category of the spurious information through the spurious vector, and output the classification result and spurious information; then return to step (2) to continue the frequency sweep;

[0012] (5) Set the new broadband inverter frequency F to be tested rf , repeat steps (2)-(4) until all frequencies of the broadband inverter to be tested are analyzed.

[0013] Furthermore, the frequency conversion relationship C is: spurs =C(F rf ,F if ,F sweep );The stray equations are:

[0014]

[0015] Among them, LO1~LO n-1 For a specific F rf and F if , the specific local oscillator frequency obtained by the determined frequency conversion relationship, s1~s n F sweep The order of each local oscillator, S = [s1 … s n ] T is a stray vector.

[0016] Furthermore, in step (4), the category of the spurious signal is analyzed by using the spurious vector. Specifically, the spurious vector is compared with each item in the spurious classification table to obtain the category to which the spurious signal belongs. The spurious classification table is prepared in advance and contains the corresponding relationship between each type of spurious signal of the specific broadband converter to be tested and its spurious vector.

[0017] The beneficial effects of the present invention are:

[0018] 1. The present invention obtains the stray vector by solving the stray equation group, thereby realizing the classification of stray. The process only needs to set the relevant information of the frequency conversion relationship of the device under test in advance, and the subsequent process does not require manual intervention, which can replace the traditional manual test and analysis of stray.

[0019] 2. The classification of spurious signals in the present invention can cover indicators such as image frequency suppression, intermediate frequency suppression, harmonic suppression and spurious suppression, thereby obtaining a complete analysis result. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of a method according to an embodiment of the present invention.

[0021] Figure 2 Schematic diagram of an automatic testing hardware system according to an embodiment of the present invention.

[0022] Figure 3 It is a schematic diagram of the frequency response relationship of an embodiment of the present invention.

[0023] Figure 4 This is a spurious classification table corresponding to the embodiment of the present invention. DETAILED DESCRIPTION

[0024] The present invention is described in detail below in conjunction with the embodiments and drawings.

[0025] A broadband inverter spurious automatic analysis method, which is applied to Figure 2 The automatic test hardware system shown in the figure includes a host computer, a signal source, a spectrum analyzer and a device under test. This method obtains complete spurious information by sweeping the working bandwidth, solves the number of spurious combinations of the spurious that need to be concerned by the spurious analysis algorithm, and finally classifies the spurious by the number of spurious combinations. This method is not only applicable to signal-related spurious and signal-irrelevant spurious, but also to indicators such as image frequency suppression, intermediate frequency suppression, local oscillator leakage and harmonic suppression.

[0026] like Figure 1 As shown, the method mainly includes the following steps:

[0027] Automatic test for stray (A):

[0028] In the test parameter setting (A-1), the following parameters will be configured: Figure 2 The hardware system shown in the figure, the host computer runs the program to control the device under test to work at the receiving frequency F rf , output intermediate frequency F if , working bandwidth status BW if , spectrum analyzer monitoring frequency range F if ±BWif / 2.

[0029] In the stray automatic scanning test (A-2), the host computer controls the signal source at F sweepmin ~F sweepmax The frequency is swept within the frequency range, and the host computer monitors the spurious frequency F obtained by the test through the spectrum analyzer spurs and amplitude P spurs .

[0030] In the judgment process (A-3), according to the set threshold value P threshold Judge P spurs Is it greater than P threshold , if P is satisfied spurs ≥P threshold Then proceed to the solution of the spurious combination (B). If it is not satisfied, go back to the scan test.

[0031] Solution for spurious combination (B):

[0032] In constructing the spurious equation set (B-1), the frequency conversion function F corresponding to the hardware design of the device under test is used. spurs =C(F rf ,F if ,F sweep ) and the spurious related information obtained in step (A), construct the equation system shown in equation (1):

[0033]

[0034] Among them, for a specific F rf and F if , the specific local oscillator frequency LO1~LO can be obtained by determining the frequency conversion relationship n-1 , stray vector S = [s1 … s n ] T F sweep And the order of each level of local oscillator.

[0035] In solving the spurious equation group (B-2), the n-variable linear equation group defined by equation (1) is solved to obtain a spurious vector S of a specific spurious signal, which is provided to the spurious classification (C) step.

[0036] Spurious classification (C):

[0037] In the spurious classification step (C-1), a spurious classification table can be obtained according to the determined frequency conversion relationship, and the classification to which the spurious belongs can be obtained by comparing the obtained spurious vector S with each item in the spurious classification table.

[0038] In the result output (C-2), the relevant information of the spurious is swept through the frequency F sweep、DUT configuration frequency F rf , intermediate frequency F if , spurious frequency F spurs , spurious amplitude P spurs The spurious vector S is stored and output, and the process returns to the spurious automatic frequency sweep test (A-2) step.

[0039] Here is a more specific example:

[0040] This embodiment is based on Figure 1 Specific process, for the working frequency range F rfmin ~F rfmax It is a broadband downconverter with a frequency range of 8 GHz to 12 GHz. The signal source sweep output frequency range is F sweepmin ~F sweepmax Analyze the intermediate frequency range F from 6GHz to 14GHz and spectrum analyzer if ±BW if / 2 is 1.5GHz±250MHz, according to Figure 1 Process Settings Figure 2 The test hardware system is shown.

[0041] The frequency conversion relationship adopted by the broadband down converter is as follows: Figure 3 As shown, the secondary frequency conversion scheme is adopted. Both the first local oscillator LO1 and the second local oscillator LO2 are selected to be high local oscillators. The first intermediate frequency is 4.3 GHz. According to the operating frequency range, it can be known that the frequency range of the first local oscillator is 12.3 GHz to 16.3 GHz, and the second local oscillator is 5.8 GHz. According to this frequency conversion relationship, the normal frequency conversion satisfies formula (2):

[0042] F rf -LO1(F rf )+LO2(F rf )=F if (2)

[0043] Furthermore, the frequency conversion function (3) can be obtained for a specific spurious signal. The three-variable linear equation system shown in equation (4) can be constructed by equation (3). The spurious signal vector S can be obtained by solving equation (4).

[0044] F spurs =C(F rf ,F if ,F sweep )=s1·F sweep +s2·LO1(F rf )+s3·LO2(F rf ) (3)

[0045]

[0046] Then, the obtained spurious vector S is Figure 4 By comparing the spurious classification table shown in the figure, the classification of the specific spurious can be obtained. Store the relevant sweep frequency F sweep 、DUT configuration frequency F rf , intermediate frequency F if , spurious frequency F spurs , spurious amplitude P spurs After obtaining information such as the spurious vector S, the frequency sweep test can be continued.

[0047] In summary, the present invention realizes the extraction and analysis of the spurious information of the broadband frequency converter through three steps: automatic testing of spurious information, solving the spurious combination structure and classifying spurious information. The extraction and analysis cover the indicators of image frequency suppression, intermediate frequency suppression, harmonic suppression and spurious suppression. The method can improve the research and development and testing efficiency of the broadband frequency converter.

Claims

1. A broadband inverter spurious automatic analysis method, characterized in that: Applied to the stray automatic test system; the stray automatic test system includes a broadband frequency converter to be tested, a signal source, a host computer and a spectrum analyzer; wherein the operating frequency range of the broadband frequency converter to be tested is F rfmin ~F rfmax , the sweep output frequency range of the signal source is F sweepmin ~F sweepmax The range of intermediate frequencies that can be analyzed by the spectrum analyzer is [F if ±BW if / 2],F if is the intermediate frequency, BW if is the intermediate frequency bandwidth; The following steps are involved: (1) Set the frequency F of the broadband inverter to be tested rf , F rf ∈F rfmin ~F rfmax ; (2) The signal source is at F sweepmin ~F sweepmax The frequency is swept within the range, and the spectrum analyzer measures the spurious frequency F spurs and the spurious amplitude P spurs ; If the spurious amplitude P spurs Exceeding the threshold P threshold , then record the current sweep frequency F sweep , spurious frequency F spurs and the spurious amplitude P spurs , then execute steps (3) and (4); complete F sweepmin ~F sweepmax After sweeping within the range, go to step (5); (3) Using the frequency conversion relationship of the broadband frequency converter to be tested, a set of spurious equations is constructed and solved to obtain a spurious vector; the frequency conversion relationship C is: spurs =C(F rf ,F if ,F sweep ); The stray equations are: Among them, LO1~LO n-1 For a specific F rf and F if , the specific local oscillator frequency obtained by the determined frequency conversion relationship, s1~s n F sweep The order of each local oscillator, S = [s1…s n ] T is a stray vector; (4) Analyze the category of the spurious information through the spurious vector, and output the classification result and spurious information; then return to step (2) to continue the frequency sweep; (5) Set the new broadband inverter frequency F to be tested rf , repeat steps (2)-(4) until all frequencies of the broadband inverter to be tested are analyzed.

2. The method for automatic spurious analysis of a broadband frequency converter according to claim 1, characterized in that: In step (4), the category of the spurious signal is analyzed by using a spurious vector. Specifically, the spurious vector is compared with each item in a spurious classification table to obtain the category to which the spurious signal belongs. The spurious classification table is prepared in advance and contains the corresponding relationship between each type of spurious signal of the specific broadband converter to be tested and its spurious vector.

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