Article(id=1315741665097265784, tenantId=1146029695717560320, journalId=1315121910733963395, issueId=1315741514865689424, articleNumber=null, orderNo=null, doi=10.3788/gzxb20265503.0312002, pmid=null, cstr=32255.14.gzxb20265503.0312002, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1762099200000, receivedDateStr=2025-11-03, revisedDate=null, revisedDateStr=null, acceptedDate=1767110400000, acceptedDateStr=2025-12-31, onlineDate=1791626858256, onlineDateStr=2026-10-10, pubDate=1774368000000, pubDateStr=2026-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791626858256, onlineIssueDateStr=2026-10-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791626858256, creator=13701087609, updateTime=1791626858256, updator=13701087609, issue=Issue{id=1315741514865689424, tenantId=1146029695717560320, journalId=1315121910733963395, year='2026', volume='55', issue='3', pageStart='1', pageEnd='378', issueExtLink='null', onlineDate='null', pubDate='1774368000000', pubDateStr='2026-03-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1791626822438, creator='13701087609', updateTime=1791626932547, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1315741977111540218, tenantId=1146029695717560320, journalId=1315121910733963395, issueId=1315741514865689424, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1315741977111540219, tenantId=1146029695717560320, journalId=1315121910733963395, issueId=1315741514865689424, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=319, endPage=339, ext={EN=ArticleExt(id=1315741666577855100, articleId=1315741665097265784, tenantId=1146029695717560320, journalId=1315121910733963395, language=EN, title=An FPGA-based Real-time Laser Interferometric Length Measurement System with Point-by-point Phase Computation, columnId=1315741666489774715, journalTitle=Acta Photonica Sinica, columnName=Instrumentation, Measurement and Metrology, runingTitle=null, highlight=null, articleAbstract=

With the rapid development of precision manufacturing, semiconductor lithography, and aerospace engineering, ultra-precision machining and metrology have placed higher demands on micro-displacement measurement systems that combine nanometer-level precision with high-bandwidth real-time performance. In dynamic, high-speed motion scenarios, such systems not only need to achieve extremely high resolution but also provide low-latency data processing at high sampling rates. As a fundamental technology in modern length metrology, laser interferometry has inherent advantages in terms of accuracy and stability. However, traditional software-based processing architectures rely on CPUs and sequential execution models, often encountering severe computational bottlenecks when processing high-speed interferometric signals. These limitations make it difficult to simultaneously meet the conflicting demands of large measurement range, high resolution, and real-time detection. To overcome these challenges, this paper proposes a single-frequency laser displacement measurement system based on FPGA, which integrates an FPGA platform and a high-performance point-by-point phase calculation algorithm. By transferring the signal processing algorithm from software to a dedicated hardware logic platform and employing parallel computing and a pipelined approach, the system significantly improves real-time performance while maintaining nanometer-level measurement accuracy.

First, this paper establishes a four-channel orthogonal laser interferometry structure and develops a real-time phase demodulation method based on the phase difference between adjacent sampling points. By introducing phase jump correction and cumulative phase compensation mechanisms, the algorithm effectively solves the problems of phase unwrapping ambiguity and displacement direction discrimination under high-speed motion conditions, thereby ensuring the continuity and robustness of displacement measurement. Meanwhile, to analyze the impact of non-ideal optical elements on nonlinear errors, this paper constructs a systematic error model using Jones matrix theory. This model quantitatively analyzes the effects of waveplate angle misalignment and Polarization Beam Splitter (PBS) splitting ratio imbalance on the interference signal, revealing their roles in introducing DC offset, amplitude mismatch, and non-orthogonality between orthogonal channels. Based on this analysis, this paper designs a vector-based error compensation algorithm to correct these defects, thereby significantly improving phase linearity and overall measurement accuracy. Based on the proposed algorithm, a complete experimental test platform was established, and a host-computer-based multi-threaded displacement measurement software was developed to evaluate the system performance. Experimental results demonstrate that, within a measurement range of 200 μm, the system achieves a statistical measurement accuracy better than 10 nm while supporting millisecond-level data update rates, thereby validating the effectiveness and practicality of the proposed method.

Based on the validated theoretical and software framework, this paper further develops an FPGA hardware system integrating a high-speed multi-channel ADC to comprehensively enhance real-time processing capabilities. By employing a fully pipelined architecture and dedicated parallel processing units, key algorithms such as error compensation and phase demodulation are transformed into hardware logic. This hardware-oriented design ensures stable and predictable computational latency, which is crucial for real-time measurement. Experimental comparisons show that the results of the FPGA-based hardware processing are in high agreement with the results of the host multi-threaded software algorithm, with a Root Mean Square Error (RMSE) of only 9.16 nm and statistical accuracy consistently maintained within 10 nm. Real-time performance evaluation further validates the advantages of the proposed system. The initial processing latency is reduced to 10.4 μs, and the displacement data update cycle reaches 100 ns. Therefore, the system can reconstruct complete micrometer-level motion trajectories in real time within 1 millisecond, representing a significant performance improvement compared to traditional CPU-based processing architectures. These performance characteristics make the system particularly suitable for applications such as high-speed motion, dynamic vibration monitoring, and real-time feedback control.

In summary, this paper proposes a laser interferometric real-time displacement measurement system by deeply integrating a point-by-point phase demodulation algorithm and FPGA-based hardware acceleration technology. This system simultaneously achieves high precision, high stability, and ultra-fast real-time performance. It provides a reliable and high-performance metrology solution for closed-loop motion control, dynamic vibration analysis, and nanometer-level precision positioning in ultra-precision engineering applications, demonstrating significant practical value and broad application prospects.

, authors=Jinyu LI, Zhenyan GUO, Zhishan GAO, Qiqi YU, Junhao KUANG, Hao LI, authorsList=Jinyu LI, Zhenyan GUO, Zhishan GAO, Qiqi YU, Junhao KUANG, Hao LI, authorCompany=null, correspAuthors=Zhenyan GUO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1315741676266697396, articleId=1315741665097265784, tenantId=1146029695717560320, journalId=1315121910733963395, language=CN, title=基于FPGA的逐点计算实时激光干涉测长研究, columnId=1315741666716267133, journalTitle=光子学报, columnName=仪器,测量,度量学, runingTitle=null, highlight=null, articleAbstract=

提出一种基于现场可编程门阵列(FPGA)的逐点计算激光干涉测长系统,通过相邻采样点相位差实时计算与相位跳变修正,实现了连续、实时的位移解算。针对光学元件分光比制造误差、波片角度偏差等因素引起的非理想干涉信号问题,基于琼斯矩阵分析了系统误差,提出相应的误差校正算法提高了相位解算精度。为进一步提升系统的实时测量性能,设计并实现了基于高速模数转换器(ADC)与现场可编程门阵列的位移测量硬件系统,完成了误差校正、相位解算等关键算法的硬件并行架构设计,并通过上板实验对系统性能进行了验证。实验结果表明,该系统在实现毫秒级快速测量的同时,测量误差可控制在10 nm以内;系统首个数据延迟约为10.4 μs,数据更新周期缩短至100 ns。该位移测量系统在保证纳米级测量精度的前提下,可实现微秒级响应与实时解算,兼顾高精度与高实时性,适用于高速精密位移测量场景。

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journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Fig.13, caption=Flow chart of direction discrimination and accµmulation module, figureFileSmall=e4uNhjygd92SK+JylVtaTw==, figureFileBig=+IrhccNnHgnLJfKlMljHRQ==, tableContent=null), ArticleFig(id=1315741684978266876, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=图13, caption=辨向及累加模块流程图, figureFileSmall=e4uNhjygd92SK+JylVtaTw==, figureFileBig=+IrhccNnHgnLJfKlMljHRQ==, tableContent=null), ArticleFig(id=1315741685187982078, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Fig.14, caption=Waveform diagram of direction discrimination and accµmulation module, figureFileSmall=/9D4RfUQRdMeyJWcANydkQ==, figureFileBig=O7NVAsmUnn1EBz2qj/hksw==, tableContent=null), ArticleFig(id=1315741685271868159, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=图14, caption=辨向以及累加模块波形图, figureFileSmall=/9D4RfUQRdMeyJWcANydkQ==, figureFileBig=O7NVAsmUnn1EBz2qj/hksw==, tableContent=null), ArticleFig(id=1315741685578052352, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Fig.15, caption=Schematic diagram of overall system hardware architecture and signal flow, figureFileSmall=YOYfbaCiF+2XVcwBv/9MIQ==, figureFileBig=QMdJ/KP2H/4mEfpqYPqsNw==, tableContent=null), ArticleFig(id=1315741685657744129, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=图15, caption=系统硬件总体架构与信号流向原理图, figureFileSmall=YOYfbaCiF+2XVcwBv/9MIQ==, figureFileBig=QMdJ/KP2H/4mEfpqYPqsNw==, tableContent=null), ArticleFig(id=1315741685750018818, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Fig.16, caption=Photograph of the hardware experimental platform for length measurement 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journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=图19, caption=ILA捕获的FPGA内部预处理后的正交信号与相位波形, figureFileSmall=hrMUpZHiclnon7Y2hWkzOA==, figureFileBig=MFk5xda8D6icPBqogygWdA==, tableContent=null), ArticleFig(id=1315741689000604427, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Fig.20, caption=ILA captured waveform of final real-time calculated displacement output, figureFileSmall=c83ftO9TyI8Y+Y84xNf8TQ==, figureFileBig=ioR7kVvqlVGHJsi9rTerUQ==, tableContent=null), ArticleFig(id=1315741689092879117, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=图20, caption=ILA捕获的最终实时位移解算输出波形, figureFileSmall=c83ftO9TyI8Y+Y84xNf8TQ==, figureFileBig=ioR7kVvqlVGHJsi9rTerUQ==, tableContent=null), ArticleFig(id=1315741689357120270, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Fig.21, 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caption=Matlab浮点与FPGA定点位移解算结果对比及误差分析, figureFileSmall=KhchLVkVXW60/lN6fgoKDQ==, figureFileBig=rMZY+eWb9vo6Sa3Siza49Q==, tableContent=null), ArticleFig(id=1315741690183398163, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Fig.23, caption=Distribution plot of deviation between matlab and FPGA calculations versus displacement, figureFileSmall=VGyV6ilQMfPfMUSdUAyDow==, figureFileBig=vI4+aoQobVazAEe7zPtaPA==, tableContent=null), ArticleFig(id=1315741690250507028, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=图23, caption=Matlab与FPGA解算偏差随位移变化的分布, figureFileSmall=VGyV6ilQMfPfMUSdUAyDow==, figureFileBig=vI4+aoQobVazAEe7zPtaPA==, tableContent=null), ArticleFig(id=1315741690330198805, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table1, caption=

Displacement measurement error under different velocity conditions.

, figureFileSmall=null, figureFileBig=null, tableContent=
Velocity1 mm/s3 mm/s5 mm/s10 mm/s15 mm/s
Error0.065 nm0.198 nm0.332 nm0.664 nm0.996 nm
), ArticleFig(id=1315741690665743126, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表1, caption=

不同速度下的位移计算误差

, figureFileSmall=null, figureFileBig=null, tableContent=
Velocity1 mm/s3 mm/s5 mm/s10 mm/s15 mm/s
Error0.065 nm0.198 nm0.332 nm0.664 nm0.996 nm
), ArticleFig(id=1315741690741240599, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table 2, caption=

The alternating current amplitude of Icos when the angle of half - wave plate 2 changes

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle17.5°18.5°19.5°20.5°21.5°22.5°23.5°24.5°25.5°26.5°27.5°
Alternating current1.879 31.922 51.956 71.981 01.995 52.000 01.995 51.981 01.956 71.922 51.879 3
), ArticleFig(id=1315741691030647576, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表2, caption=

HWP2角度变化时的Icos的交流幅值

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle17.5°18.5°19.5°20.5°21.5°22.5°23.5°24.5°25.5°26.5°27.5°
Alternating current1.879 31.922 51.956 71.981 01.995 52.000 01.995 51.981 01.956 71.922 51.879 3
), ArticleFig(id=1315741691101950745, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table 3, caption=

The alternating current amplitude of Isin when the angle of quarter-wave plate 3 changes

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle40°41°42°43°44°45°46°47°48°49°50°
Alternating current1.999 11.999 51.999 92.000 02.000 02.000 02.000 02.000 01.999 91.999 61.999 1
), ArticleFig(id=1315741691487826714, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表3, caption=

QWP3角度变化时的Isin交流幅值

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle40°41°42°43°44°45°46°47°48°49°50°
Alternating current1.999 11.999 51.999 92.000 02.000 02.000 02.000 02.000 01.999 91.999 61.999 1
), ArticleFig(id=1315741693152965403, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table 4, caption=

The DC bias of Icos when the angle of quarter-wave plate 2 changes

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle40°41°42°43°44°45°46°47°48°49°50°
Direct current0.038 00.030 60.023 10.015 60.007 60-0.007 6-0.015 5-0.023 1-0.030 6-0.038 0
), ArticleFig(id=1315741693253628700, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表4, caption=

QWP2角度变化时的Icos的直流偏置

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle40°41°42°43°44°45°46°47°48°49°50°
Direct current0.038 00.030 60.023 10.015 60.007 60-0.007 6-0.015 5-0.023 1-0.030 6-0.038 0
), ArticleFig(id=1315741693564007197, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table 5, caption=

The alternating current amplitude of Icos, Isinwhen the angle of quarter-wave plate 2 changes

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle40°41°42°43°44°45°46°47°48°49°50°
Icos alternating current0.984 80.990 30.994 50.997 60.999 410.999 40.997 60.994 50.990 30.984 8
Isin alternating current0.984 80.990 30.994 50.997 60.999 410.999 40.997 60.994 50.990 30.984 8
), ArticleFig(id=1315741693652087582, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表5, caption=

QWP2角度变化时的Icos、Isin的交流幅值

, figureFileSmall=null, figureFileBig=null, tableContent=
Fast-axis angle40°41°42°43°44°45°46°47°48°49°50°
Icos alternating current0.984 80.990 30.994 50.997 60.999 410.999 40.997 60.994 50.990 30.984 8
Isin alternating current0.984 80.990 30.994 50.997 60.999 410.999 40.997 60.994 50.990 30.984 8
), ArticleFig(id=1315741693975048991, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table 6, caption=

The results of the system measurement accuracy

, figureFileSmall=null, figureFileBig=null, tableContent=
Measurement numberNominal value/µmCalculated value/µmError/nm
1200.001 4200.012 411
2200.001 5199.991 6-9.9
3199.999 3200.008 79.4
4200.000 9200.011 310.4
5200.001 5199.996 5-5
6200.000 7200.013 713
7199.999 7199.995 9-3.8
8199.999 5200.008 28.7
9200.001 0200.011 310.3
10200.001 7199.999 0-2.7
), ArticleFig(id=1315741694054740768, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表6, caption=

系统测量精度结果

, figureFileSmall=null, figureFileBig=null, tableContent=
Measurement numberNominal value/µmCalculated value/µmError/nm
1200.001 4200.012 411
2200.001 5199.991 6-9.9
3199.999 3200.008 79.4
4200.000 9200.011 310.4
5200.001 5199.996 5-5
6200.000 7200.013 713
7199.999 7199.995 9-3.8
8199.999 5200.008 28.7
9200.001 0200.011 310.3
10200.001 7199.999 0-2.7
), ArticleFig(id=1315741694159598369, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table 7, caption=

Statistics of time consµmption for single-batch data acquisition and processing

, figureFileSmall=null, figureFileBig=null, tableContent=
Module nameAverage time/sStandard deviation/sVariance/s2Time range/s
Acquisition0.7740.1850.034 10.505~1.342
Calculation0.3170.0710.005 10.282~0.604
), ArticleFig(id=1315741694226707234, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表7, caption=

采集与计算模块单批数据处理耗时统计

, figureFileSmall=null, figureFileBig=null, tableContent=
Module nameAverage time/sStandard deviation/sVariance/s2Time range/s
Acquisition0.7740.1850.034 10.505~1.342
Calculation0.3170.0710.005 10.282~0.604
), ArticleFig(id=1315741694411256611, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=EN, label=Table7, caption=

Comparison of calculation results between host computer and FPGA

, figureFileSmall=null, figureFileBig=null, tableContent=
Measurement numberNominal value/µmHost value/µmFPGA value/µmError/nm
1200.001200.014 5200.016 31.8
2199.999 4199.990 8199.988 5-2.3
3200.000 8200.008 2200.006-2.2
4200.000 1200.008 5200.008 3-0.2
5199.998 9199.993 5199.995 72.2
6200.001 5199.992 8199.991 1-1.7
7200.000 4199.990 1199.991 51.4
8199.999 2199.985 8199.9860.2
9200.001 8200.008 6200.007-1.6
10200.000 6199.993 4199.994 20.8
11199.998 8200.009 1200.007 9-1.2
12200.001 1200.009 3200.006 8-2.5
13199.999 6200.006 2200.006-0.2
14200.000 9199.990 8199.988 6-2.2
15200.000 4200.007 5200.008 40.9
), ArticleFig(id=1315741694482559780, tenantId=1146029695717560320, journalId=1315121910733963395, articleId=1315741665097265784, language=CN, label=表7, caption=

上位机和FPGA计算结果对比

, figureFileSmall=null, figureFileBig=null, tableContent=
Measurement numberNominal value/µmHost value/µmFPGA value/µmError/nm
1200.001200.014 5200.016 31.8
2199.999 4199.990 8199.988 5-2.3
3200.000 8200.008 2200.006-2.2
4200.000 1200.008 5200.008 3-0.2
5199.998 9199.993 5199.995 72.2
6200.001 5199.992 8199.991 1-1.7
7200.000 4199.990 1199.991 51.4
8199.999 2199.985 8199.9860.2
9200.001 8200.008 6200.007-1.6
10200.000 6199.993 4199.994 20.8
11199.998 8200.009 1200.007 9-1.2
12200.001 1200.009 3200.006 8-2.5
13199.999 6200.006 2200.006-0.2
14200.000 9199.990 8199.988 6-2.2
15200.000 4200.007 5200.008 40.9
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基于FPGA的逐点计算实时激光干涉测长研究
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李金宇 , 郭珍艳 , 高志山 , 喻琪琪 , 匡俊豪 , 李昊
光子学报 | 仪器,测量,度量学 2026,55(3): 319-339
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光子学报 |仪器,测量,度量学 2026 , 55 (3) : 319 -339
基于FPGA的逐点计算实时激光干涉测长研究
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李金宇 , 郭珍艳 , 高志山, 喻琪琪, 匡俊豪, 李昊
作者信息
  • 1南京理工大学 电子工程与光电技术学院, 南京 210094
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作者简介:
An FPGA-based Real-time Laser Interferometric Length Measurement System with Point-by-point Phase Computation
Jinyu LI , Zhenyan GUO , Zhishan GAO, Qiqi YU, Junhao KUANG, Hao LI
Affiliations
  • 1School of Electronic Engineering and Optoelectronic Technology , Nanjing University of Science and Technology, Nanjing 210094, China
出版时间: 2026-03-25 doi: 10.3788/gzxb20265503.0312002
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提出一种基于现场可编程门阵列(FPGA)的逐点计算激光干涉测长系统,通过相邻采样点相位差实时计算与相位跳变修正,实现了连续、实时的位移解算。针对光学元件分光比制造误差、波片角度偏差等因素引起的非理想干涉信号问题,基于琼斯矩阵分析了系统误差,提出相应的误差校正算法提高了相位解算精度。为进一步提升系统的实时测量性能,设计并实现了基于高速模数转换器(ADC)与现场可编程门阵列的位移测量硬件系统,完成了误差校正、相位解算等关键算法的硬件并行架构设计,并通过上板实验对系统性能进行了验证。实验结果表明,该系统在实现毫秒级快速测量的同时,测量误差可控制在10 nm以内;系统首个数据延迟约为10.4 μs,数据更新周期缩短至100 ns。该位移测量系统在保证纳米级测量精度的前提下,可实现微秒级响应与实时解算,兼顾高精度与高实时性,适用于高速精密位移测量场景。

激光干涉测长  /  四路正交零差  /  实时位移解算  /  非线性误差校正  /  现场可编程门阵列

With the rapid development of precision manufacturing, semiconductor lithography, and aerospace engineering, ultra-precision machining and metrology have placed higher demands on micro-displacement measurement systems that combine nanometer-level precision with high-bandwidth real-time performance. In dynamic, high-speed motion scenarios, such systems not only need to achieve extremely high resolution but also provide low-latency data processing at high sampling rates. As a fundamental technology in modern length metrology, laser interferometry has inherent advantages in terms of accuracy and stability. However, traditional software-based processing architectures rely on CPUs and sequential execution models, often encountering severe computational bottlenecks when processing high-speed interferometric signals. These limitations make it difficult to simultaneously meet the conflicting demands of large measurement range, high resolution, and real-time detection. To overcome these challenges, this paper proposes a single-frequency laser displacement measurement system based on FPGA, which integrates an FPGA platform and a high-performance point-by-point phase calculation algorithm. By transferring the signal processing algorithm from software to a dedicated hardware logic platform and employing parallel computing and a pipelined approach, the system significantly improves real-time performance while maintaining nanometer-level measurement accuracy.

First, this paper establishes a four-channel orthogonal laser interferometry structure and develops a real-time phase demodulation method based on the phase difference between adjacent sampling points. By introducing phase jump correction and cumulative phase compensation mechanisms, the algorithm effectively solves the problems of phase unwrapping ambiguity and displacement direction discrimination under high-speed motion conditions, thereby ensuring the continuity and robustness of displacement measurement. Meanwhile, to analyze the impact of non-ideal optical elements on nonlinear errors, this paper constructs a systematic error model using Jones matrix theory. This model quantitatively analyzes the effects of waveplate angle misalignment and Polarization Beam Splitter (PBS) splitting ratio imbalance on the interference signal, revealing their roles in introducing DC offset, amplitude mismatch, and non-orthogonality between orthogonal channels. Based on this analysis, this paper designs a vector-based error compensation algorithm to correct these defects, thereby significantly improving phase linearity and overall measurement accuracy. Based on the proposed algorithm, a complete experimental test platform was established, and a host-computer-based multi-threaded displacement measurement software was developed to evaluate the system performance. Experimental results demonstrate that, within a measurement range of 200 μm, the system achieves a statistical measurement accuracy better than 10 nm while supporting millisecond-level data update rates, thereby validating the effectiveness and practicality of the proposed method.

Based on the validated theoretical and software framework, this paper further develops an FPGA hardware system integrating a high-speed multi-channel ADC to comprehensively enhance real-time processing capabilities. By employing a fully pipelined architecture and dedicated parallel processing units, key algorithms such as error compensation and phase demodulation are transformed into hardware logic. This hardware-oriented design ensures stable and predictable computational latency, which is crucial for real-time measurement. Experimental comparisons show that the results of the FPGA-based hardware processing are in high agreement with the results of the host multi-threaded software algorithm, with a Root Mean Square Error (RMSE) of only 9.16 nm and statistical accuracy consistently maintained within 10 nm. Real-time performance evaluation further validates the advantages of the proposed system. The initial processing latency is reduced to 10.4 μs, and the displacement data update cycle reaches 100 ns. Therefore, the system can reconstruct complete micrometer-level motion trajectories in real time within 1 millisecond, representing a significant performance improvement compared to traditional CPU-based processing architectures. These performance characteristics make the system particularly suitable for applications such as high-speed motion, dynamic vibration monitoring, and real-time feedback control.

In summary, this paper proposes a laser interferometric real-time displacement measurement system by deeply integrating a point-by-point phase demodulation algorithm and FPGA-based hardware acceleration technology. This system simultaneously achieves high precision, high stability, and ultra-fast real-time performance. It provides a reliable and high-performance metrology solution for closed-loop motion control, dynamic vibration analysis, and nanometer-level precision positioning in ultra-precision engineering applications, demonstrating significant practical value and broad application prospects.

Laser interferometry  /  Quadrature homodyne  /  Real-time displacement  /  Error correction  /  FPGA
李金宇, 郭珍艳, 高志山, 喻琪琪, 匡俊豪, 李昊. 基于FPGA的逐点计算实时激光干涉测长研究. 光子学报, 2026 , 55 (3) : 319 -339 . DOI: 10.3788/gzxb20265503.0312002
Jinyu LI, Zhenyan GUO, Zhishan GAO, Qiqi YU, Junhao KUANG, Hao LI. An FPGA-based Real-time Laser Interferometric Length Measurement System with Point-by-point Phase Computation[J]. Acta Photonica Sinica, 2026 , 55 (3) : 319 -339 . DOI: 10.3788/gzxb20265503.0312002
随着纳米加工、精密制造、精密装配等行业的发展,对高精度微位移的测量需求日益增长。光学微位移测量技术[1]因其高分辨率、高重复性、高稳定性的测量优势,已广泛应用于半导体制造、精密仪器制造、微纳操作等领域。其中,激光干涉测距方法凭借其非接触式测量模式,可同时实现高速率与高精度的特性,成为高精密测距的主要方法[2]。
激光干涉测距技术主要包括单频激光干涉和双频激光干涉方法。双频激光干涉测距通过声光调制或塞曼效应产生频差,采用多普勒频移技术对位移量进行测量,常用于超精密加工,如光刻机高精度位移台定位、精密数控机床等领域[3]。双频激光干涉测距精度高且抗干扰能力强,但测量速度易受频差影响,同时频率混叠现象也会造成较大的非线性误差[4]。单频激光干涉以传统的迈克尔逊干涉为基础,增加一路干涉输出形成正交信号,由干涉条纹的周期数反演位移。其成本低、结构紧凑、测量分辨率高,测量速度在理论上没有明确限制[5]。在此基础上,四路正交零差干涉通过引入偏振分束器、相位延迟元件等光学器件,构建差分信号,使系统抗干扰能力得到显著提升[6],再结合误差校正与相位解算算法,减小非线性误差,可实现高分辨率、高精度的纳米级测量[7-8]。常用的误差校正算法包括椭圆拟合法[9-10]、最小二乘法[11]和矢量法。椭圆拟合法和最小二乘法可实现较高的修正精度,但均依赖大量采样数据进行拟合计算,且算法复杂度较高,难以在硬件上高效实现,特别在实时性要求较高的测量场景中存在明显不足[12]。而矢量法通过建立矢量方程进行修正,可消除分光元件分光比制造误差、波片角度偏差带来的非线性误差,运算简单、抗干扰性能较强,可显著提升测量场景实时性能。
传统的相位细分解算算法在实时性方面同样存在局限。该方法通过将干涉条纹的一个周期划分为若干区间,结合反正切计算实现相位解算,获得亚周期级的分辨率[13],该算法通常依赖完整干涉周期的判别与累积处理,其实时性和动态响应能力受到明显限制,难以满足高速动态位移测量的需求[14]。针对上述问题,本文提出了一种基于FPGA和逐点相位差计算的四路正交零差激光干涉系统,旨在实现位移的高速实时解算。该方法以高速ADC采集的单点干涉信号为输入,通过在FPGA内对相邻采样点相位进行实时计算,获得逐点相位差,并结合相位解包裹算法与位移方向判别机制,实现无需完整干涉周期判别的连续位移解算。在此基础上,针对四路正交非理想干涉信号在实际测量系统中存在的误差,系统在FPGA内部集成了在线误差校正模块,采用流水线架构对干涉信号进行实时校正。通过上述处理,系统在FPGA硬件平台上完成了从信号采集、误差修正、相位差计算到位移解算的全流程并行化实时处理,显著降低了系统延迟,提升了动态测量场景下的实时性与稳定性,为高速精密位移测量提供了一种高效的技术方案。
在此基础上,本文围绕其关键问题开展了系统性研究,旨在提升系统的实时处理能力与测量精度。具体工作包括:深入研究基于逐点计算算法的四路正交零差激光干涉测长技术,设计并搭建光路系统,开发基于逐点计算的位移测量相位解算算法;建立误差模型进行模拟分析,改进误差校正算法,同时搭建测试平台验证激光干涉测距系统的测量精度与实时性;设计并建立基于FPGA的实时处理硬件系统,实现高精度、高实时性、低非线性误差的位移测量。
四路正交零差激光干涉测长光路是基于共模抑制原理,通过在光路中引入偏振分束器和相位延迟器件,将干涉信号调制为四路两两正交且误差分布一致的输出。对四路信号进行差分运算,可消除共模噪声,得到理想的正交干涉信号。系统光路结构如图1所示。
其中,He-Ne激光器发射的线偏振光首先通过半波片(Half Wave Plate, HWP)1进行偏振方向调整后进入偏振分光棱镜(Polarizing Beam Splitter, PBS)1并被分成振动方向相互垂直的两路线偏振光。其中反射光为垂直光(S-polarized light, S光),透射光为平行光(P-polarized light, P光)。S偏振光经过四分之一波片(Quarter Wave Plate, QWP)1被调制成圆偏振光入射到参考角锥棱镜,反射后再次通过QWP1重新变为线偏振光,但偏振方向相对旋转了90°,即从S偏振光变成了P偏振光;与此同时,P偏振光经过QWP2后入射到测试角锥棱镜,并被测试角锥棱镜反射后变成了S偏振光。而后两束震动方向相互垂直的线偏振光经过非偏振分光棱镜(Non-Polarizing Beam Splitter, NPBS)后等分为透射光和反射光。反射光被QWP3转换为旋向相反、相位差90°的圆偏振光对,随后经过偏振分光镜PBS2被分解成两对线偏振光,并在光电探测器2和4的接收端发生干涉;透射光通过HWP2后形成相位差180°的圆偏振光对,经过偏振分光镜PBS3后在光电探测器1和3的接收端发生干涉。系统最终输出四路两两正交的干涉信号。
为了定量描述光场在偏振光路系统中的传播特性,结合上述光路结构分析,采用琼斯传递矩阵法来描述实验系统光路中器件的传递特性,通过将激光传播路径中各光学元件的琼斯矩阵逐一相乘,即可得到光电探测器接收面处的理想光强分布I1、I2、I3和I4为
I1=A1221+cosΦ2-Φ1
I2=A1221+cosΦ2-Φ1-π/2
I3=A1221+cosΦ2-Φ1-π
I4=A1221+cosΦ2-Φ1+π/2
对四路信号I1、I2、I3和I4分别进行差分运算可以得到两路正交的差分信号有
Icos=I1-I3=A12cosΦIsin=I2-I4=A12sinΦ
式中,Φ=Φ2-Φ1为测量光路与参考光路的相位差,相位差每变化2π,干涉条纹亮暗就变化一次,光程发生一个周期的变化,因此通过计算干涉条纹的变换次数,就可以计算出测量角锥棱镜的运动距离
ΔΦ=2πλnΔ2l1-2l2
式中,λ为光源的波长参数,n为空气介质折射率,l1、l2分别为参考壁和测试臂的物理路径。对式(6)进行转换,可得
Δl=ΔΦλ4πn
综上可知,用两路正交信号的光强值可以计算出相位的变换量,从而可以求得两臂的实时物理路径差。
在实际测量中,仅依赖干涉条纹的计数难以满足纳米级分辨率的要求,需要进一步对干涉信号在一个周期内的相位变化进行精细计算。因此,本文提出了基于逐点计算的相位解算算法,用于纳米级位移测量。首先,利用高采样率的高速采集卡对四路正交干涉信号进行采集,并实施差分运算,经差分处理后,两路干涉信号呈现出90°的相位差特性,可以通过反正切计算求解出每个采样点的相位信息;随后,对相邻采样点的相位进行差值计算,同时采样解包裹算法进行相位展开,此外,依据相位差阈值判断被测物体的位移变化方向,进而对相位差进行针对性修正;最终,对修正后的相位差数组进行累加,以获得整个测量过程中的相位变化情况,再结合相位与光程的关系式,将其转换为精确的位移信息。具体的计算过程如下:对四路两两正交的干涉信号做差分和非线性误差修正后可以得到两路正交的干涉信号有
Isin_1=sin(Φ2_1-Φ1_1)=sinΔΦ1Icos_1=cos(Φ2_1-Φ1_1)=cosΔΦ1Isin_2=sin(Φ2_2-Φ1_2)=sinΔΦ2Icos_2=cos(Φ2_2-Φ1_2)=cosΔΦ2
式中,Φ1_1和Φ2_1分别为第一时刻参考光路和测试光路的相位,ΔΦ1为参考光路与测试光路之间的相位差Φ2_1-Φ1_1;Φ1_2和Φ2_2分别为第二时刻参考光路和测试光路的相位,ΔΦ2为第二时刻参考光路与测试光路之间的相位差Φ2_2-Φ1_2。对第一时刻和第二时刻的两路正交干涉信号分别进行反正切运算,得到对应的相位差ΔΦ1和ΔΦ2并作差,可得
ΔΦ2-1=ΔΦ2-ΔΦ1=Φ2_2-Φ1_2-Φ2_1+Φ1_1
由于参考角锥棱镜固定不动,所以Φ2_1=Φ1_1,由此得到相邻两个采样点的相位差记为
ΔΦ2-1=ΔΦ2-ΔΦ1=Φ2_2-Φ1_2
根据干涉原理,相邻两个采样点之间的相位差ΔΦ与目标位移速度v以及采样频率f之间的关系为
ΔΦ=4πvλf
式中,λ为激光光源的中心波长。为了能够无歧义地通过相位差还原真实运动,相邻两个采样点之间的相位变化量必须小于π,一旦真实相位差超过π,算法将无法区分是正向的大角度相位变化还是反向的小角度相位变化,从而导致相位混叠。
为了防止相位混叠,必须保证ΔΦ≤π。将式(11)带入该不等式,可以推导出被测物体运动速度v必须满足的条件
v≤fλ4
在满足上述条件的情况下,相邻采样点之间的相位变化是连续且微小的,因此,相邻两个采样序列之间的理论相位差值为
ΔΦ=4πλνf=nπ,n≪1
由于一般情况下相邻两个采样点之间的相位差远小于π,因此相邻采样点之间的相位差可通过相减直接获得。但由于arctan函数的输出范围限制在(-π/2,π/2),因此当干涉信号相位穿越极限点(如89°到-89°)时,相邻相位差超出该范围时,发生相位跳变。针对这类情况,需要依据被测物体运动方向进行相位展开和修正,分为以下四种情况,即
正常情况下,当待测目标向正向移动且未触及反正切函数的定义域边界时,相邻采样点的相位将单调递增。相邻采样点之间的相位差满足关系
Φi+1-Φi>0Φi+1-Φi<nπ
此时,真实的相位变化量即为两者的直接差值,无需修正。相邻两个采样序列的相位差为
ΔΦ=Φi+1-Φi
第二种情况,当待测目标向正向运动但发生跨周期现象时,数学上表现为Φi+1远小于Φi,相邻采样点之间的相位差满足关系
Φi+1-Φi<0Φi+1-Φi<-nπ
为了恢复真实的物理相位变化,需要在计算结果中加上一个完整的相位周期π。修正后的相位差公式为
ΔΦ=Φi+1-Φi+π
第三种情况,当待测目标进行反向运动时且未触及反正切函数的定义域边界时,相邻采样点的相位将单调递减。相邻采样点之间的相位差满足关系
Φi+1-Φi<0Φi+1-Φi>-nπ
此时,相位变化处于连续状态,真实的相位变化量同样直接由两者相减得到
ΔΦ=Φi+1-Φi
第四种情况,当待测目标向反向运动但发生跨周期现象时,数学上表现为Φi+1远大于Φi,相邻采样点之间的相位差满足以下关系
Φi+1-Φi>0Φi+1-Φi>nπ
为了恢复真实的物理相位变化,需要在计算结果中减去一个完整的相位周期π。修正后的相位差公式为
ΔΦ=Φi+1-Φi-π
对修正完的相位差数据进行累加计算
Φ=∑i=1nΔΦi
最后根据相位与光程的线下关系将相位信息转换成位移值,其中λ为光源的波长参数,n为空气介质折射率
L=Φλ4πn
基于解算获得的相位信息,结合式(23)即可计算出对应的位移量。为了验证理论算法的可行性,仿真设置测试角锥以1 mm/s正向运动0.05 s,接着向反方向运动同样的时间,并利用琼斯矩阵仿真整个运动过程的干涉信号变化情况,利用相位解算算法复原测试角锥的位移曲线,理想位移曲线和复原后的位移曲线如图2(a)、(b)所示。为进一步评估算法的计算精度,在固定运动时长 0.1 s 的条件下,设置了不同运动速度进行仿真,并统计各速度下的位移计算误差,计算结果如表1所示。仿真结果表明相位解算算法在原理上是可行的,理论精度可以达到亚纳米级,且可以实现方向的判别。
在对干涉信号进行相位和位移解算的环节中,理想情况下要求差分后的两路信号无直流偏置、交流幅值一致、相位正交,且为标准的正弦信号。然而在实际光路中,受外界环境噪声、光学元件加工误差、位置误差等因素的影响,信号往往并不理想,实际测得的信号中存在着交流幅值不等、直流电平分量以及额外的相位偏差。具体而言,作为光路核心组件的PBS与BS,其分光比难以达到理论设计的1∶1理想值,会直接导致两路干涉信号的能量分配不均衡。这种不均衡不仅会使信号中产生额外的直流分量,还会造成两路信号的交流幅值出现差异,为后续的相位解算与位移计算引入误差;当各元件间的光轴未严格共线时,会导致两路干涉信号的传播光程产生偏移,也会引入非线性误差;在所有影响因素中,QWP与HWP的角度误差对测量精度的影响最为显著。QWP和HWP作为核心偏振调控元件,需严格调整其快轴方向,以确保干涉信号具有良好的正交性。若波片角度存在偏差,将直接导致干涉信号的相位关系发生偏移,不仅降低正交精度,还会引起直流与交流分量的不平衡,加剧直交流偏置误差,最终影响干涉测量的准确性与稳定性。
鉴于波片角度偏差对干涉信号及测量精度的关键影响,为系统分析该偏差的作用机制与影响规律,本节基于琼斯矩阵法从理论层面推导波片角度变化对干涉信号幅值、相位特性影响的数学模型;并在理论模型的基础上,利用MATLAB数值仿真平台构建与实际光路匹配的矢量光场仿真模型,通过模拟不同角度偏差下的干涉信号输出,对理论推导结果的正确性与合理性进行验证。
与快轴呈22.5°的HWP可以使入射光束的偏振态旋转45°,产生π奇数倍的相位延迟,当HWP在性能和光路调整存在偏差时会使入射光偏振态产生变化,产生非线性误差。为了分析HWP引入的误差类型,假设经NPBS透射的参考光路和测试光路光场复振幅分别为
E0p=10,E0s=0eiΦ
式中,Φ为参考光路和测试光路的光程差。经过HWP后光场复振幅变成
Er,H=cos2θsin2θsin2θ-cos2θ10=cos2θsin2θEm,H=cos2θsin2θsin2θ-cos2θ0eiΦ=eiΦsin2θ-eiΦcos2θ
式中,θ为HWP的快轴与x轴的夹角。Er,H、Em,H经过PBS2后被分成偏振方向相互垂直的两路,并分别入射到探测器1、3上,探测器上的光功率分别为
I1=1+sin4θcosΦI3=1-sin4θcosΦ
从式(26)中发现,当θ≠22.5°时,干涉信号Icos=I1-I3的调制度下降,即交流幅值发生变化且关于22.5°对称分布;但当θ=0°或45°时,干涉条纹消失。由此可见,HWP快轴的位置偏差会增大干涉信号Icos的交流误差,且当HWP的快轴与x轴的夹角变成θ=0°或45°时,干涉信号Icos消失。
为验证推导,设置HWP的角度变化为17.5°~27.5°,利用MATLAB仿真计算干涉信号的交流幅值,结果如表1所示。从表2中可以发现,随着HWP快轴与x轴夹角从17.5°逐渐增大至22.5°,交流误差值从1.879 3逐步上升至理论最大值2;而当角度继续增大至27.5°时,误差值则对称地下降至1.879 3,其变化趋势与理论推导的交流幅值2 sin4θ的变化趋势一致。
与快轴角度呈45°的QWP使测量光束和参考光束之间引入π/2的附加相移,使四路探测器接收到的干涉信号相互正交。因此,当QWP的快轴与x轴的夹角出现偏差时,干涉信号的正交性也发生变化。假设经NPBS透射的参考光路和测试光路光场复振幅分别为E0p和E0s,经过QWP后变为
Er,Q=cos2θ+isin2θ1-icosθsinθ1-icosθsinθsin2θ+icos2θ10=cos2θ+isin2θ1-icosθsinθEm,Q=cos2θ+isin2θ1-icosθsinθ1-icosθsinθsin2θ+icos2θ0eiΦ=1-ieiΦcosθsinθ(sin2θ+icos2θ)eiΦ
式中,θ为QWP的快轴与x轴的夹角。Φ为参考光路和测试光路的光程差。Er,Q、Em,Q经过PBS3后被分成偏振方向相互垂直的两路,并分别入射到探测器上,探测器2和4的光功率分别为
I2=1-12sin4θcosΦ+sin2θsinΦI4=1+12sin4θcosΦ-sin2θsinΦ
从式(28)中发现,当θ=45°时,差θ=45°分信号Icos=I1-I3,Isin=I2-I4严格正交,而当θ≠45°时,Isin=Rsin(Φ-δθ)存在附加相移,Isin、Icos失去正交性,非正交误差变大,测长结果精度下降。而Isin的交流幅值R=4sin22θ+sin24θ在(0,45°)范围内单调上升,在θ=45°时达到极大值2,在(45°,90°)内单调下降。
设置QWP的角度为40°~50°,仿真计算角度发生偏差后的交流幅值,如表2所示。
从表3中可以发现,虽然交流幅值有变化,但波动幅度小于0.1%,与基于琼斯矩阵理论所推导出的交流幅值R=4sin22θ+sin24θ的变化情况吻合,表明QWP在一定角度容差内交流误差较小,可忽略不计。
尽管交流幅值受角度偏差的影响较小,两个差分信号Isin和Icos的正交性却随角度偏离理想状,图3展示了经过归一化处理后,在不同波片角度下的Isin和Icos所构成的李萨如图。当θ=45°时,图3(b)为标准圆,表明两路信号的相位差恰好为π/2,此时干涉信号没有非正交误差。而当θ变小时,李萨如图呈现明显的右斜椭圆化特征,表明Isin和Icos之间相位逐渐偏移;当θ变大时,李萨如图则逐渐左斜椭圆化,该现象与理论模型所呈现的非正交误差变化行为一致。
位于测试光路和参考光路的QWP1和2的作用是,使光束的偏振态发生旋转,实现参考光束和测试光束偏振态正交,而当QWP的快轴与x轴的夹角发生变化时,输出不再是严格正交的线偏振,而是椭圆偏振,对后续的光场信号产生影响。由于两个波片位置等效,因此下文只分析QWP2引入的误差。
首先假设PBS1将入射光分成两束互相正交的P光和S光,其光场复振幅分别为
EA0=10,EB0=01
为了简化计算,将光束经过QWP和角锥的往返光路过程等价为HWP对光束偏振态的调控,因此EA0和EB0到达PBS1汇合前的光场复振幅分布为
EA1=eiΦcos2(45°+δ)sin2(45°+δ)sin2(45°+δ)-cos2(45°+δ)10=eiΦ-sin2δcos2δ
EB1=10
式中,δ为QWP快轴与x轴的夹角与45°的偏差值。
EA0和EB0在PBS1汇合,并入射到NPBS被平均分为两束,透射光入射到HWP上,反射光入射到QWP上,再经PBS分束入射到四个PD探测器上,光功率分别为
I1=141+cos2δ-sin2δ2+2(cos2δ-sin2δ)cosΦI3=141+cos2δ+sin2δ2-2cos2δ+sin2δcosΦI2=12-12sin2δ-ΦI4=12-12sin2δ+Φ
从式(32)中可以计算出差分信号Isin、Icos分别为
Icos=I1-I3=cos2δcosΦ-12sin4δIsin=I2-I4=cos2δsinΦ
由式(33)可以发现,当角度偏差δ为0时,Isin和Icos为理想值,此时信号不存在直流或交流偏置,且两路信号保持严格正交关系,能够形成理想的圆形李萨如图形,实现无偏差的相位解算。而当角度偏差δ不为0,Isin出现额外的直流分量-(1/2)sin4δ,cos2δ会同时缩放Isin和Icos的交流幅值;进一步地,虽然两路信号仍然在形式上保持正交性,但由于直流偏置和幅度缩放的共同作用,李萨如图形将由理想标准圆形退化为偏心圆,且偏心圆较标准圆半径变小。
设置QWP的角度为40°~50°,并仿真计算角度发生偏差后Icos交流幅值、直流偏置和Isin的交流幅值。从表4可知QWP快轴与x轴夹角45°+δ在(40°,45°)区间内直流偏置值逐渐变小,并在δ=0时降为零,而在(45°,50°)区间内直流偏置均为负,绝对值随着角度增加而变大,且偏置分布整体关于δ=0奇对称,这与理论推导的直流偏置规律分布一致。另外,从表5中可知Icos和Isin的交流幅值在不同角度下的分布一致,且在(40°,50°)区间范围内交流幅值关于δ=0对称下降分布,这与理论推导的Icos和Isin的交流幅值cos2δ变化规律一致。
利用MATLAB获得当δ≠0时的李萨如图,如图4所示,蓝色图形为归一化前的李萨如图,红色为归一化后的李萨如图,红色圆圈为原点位置。从图中可以发现归一化前的李萨如图相较于标准圆退化成偏心圆,而在归一化消除了直交流误差后,李萨如图又回归了标准圆,说明了干涉信号并没有附加相移,QWP2角度的变化并没有影响系统的正交性。
上节已系统分析了干涉信号中存在的三类典型误差以及主要的误差来源。目前主流的误差补偿技术主要基于Heydemann提出的椭圆拟合算法。该方法是将存在三差的信号用椭圆方程来表示,然后通过数学变换公式将椭圆方程转换成标准圆方程,从而获得理想的正交干涉信号。该算法的数学对应关系明确,但计算量大,一般用于离线误差修正,无法实现实时动态误差补偿。因此,为了提高非线性误差修正算法的实时性,必须大幅度减少修正算法的计算量。椭圆拟合算法是将三种非线性误差同时消除,但如果分别计算三种类型的误差并一一消除则可以大大减少计算量。由上文可知,实际干涉信号的非线性误差一般分别三种:直流偏置、交流不等幅误差以及非正交误差,其数学形式可表示为
u1=R1cosφ+pu2=R2sinφ+δ+q
由式(34)可得
u1 max=R1+p,u1 min=-R1+pu2 max=R2+q,u2 min=-R2+q
从式(34)和式(35)可以发现,干涉信号的直流偏置p、q,交流不等幅系数R1、R2与干涉信号的极大值和极小值有关。因此根据两路干涉的信号的极大值和极小值,即可求出干涉信号的直流偏置误差和交流不等幅系数
p=u1 max+u1 min2q=u2 max+u2 min2
R1=u1 max-u1 min2R2=u2 max-u2 min2
由此直流偏置和交流不等幅误差得以校正,校正后的干涉信号数学表征公式为
U1=R2u1-p=R1R2cosφU2=R1u2-q=R1R2sinφ+δ
经过上述的计算,直流偏置和交流不等幅误差已经被修正,只剩非正交误差,表示为
Ix=RxcosφIy=Rysinφ+δ=Rycosφ+δ-π2
式中,Rx、Ry是Ix、Iy的最大幅值,且Rx=Ry。为了使消除非正交误差更具有普适性,假设Rx、Ry不等,同时再引入一个量Rxy,它为Ix+Iy的最大值,其数学表达式为
Rxy=maxIx+Iy
分别定义两个向量Rx、Ry表示干涉信号Ix、Iy,其中Rx、Ry的长度分别为Rx、Ry,两个向量之间始终相差一个恒定的相位值π/2-δ,随着相位φ的变化,向量Rx、Ry始终绕原点旋转,示意图见图5。因此干涉信号Ix、Iy的光强值为向量Rx、Ry在x轴上的投影,Rxy为Rx和Ry的合成向量,当相位φ发生变化时,Rxy的大小和方向也发生相应的变化,因此总存在一个值φ使得Rxy与x轴平行,此时Rxy的大小为maxIx+Iy,角度δ+π/2通过余弦定理计算可得
cosπ2+δ=Rx2+Ry2-Rxy22RxRy
对于任意的Rx、Ry,函数Rxyδ在-π/2≤δ≤π/2的范围内是单调的,从而得到
δ=arcsinRxy2-Rx2-Ry22RxRy
由于Rxy和Rx、Ry的值可以很容易地从测量数据中确定,因此能够精确计算出非正交误差δ的值,从而消除正交信号之间的非正交误差。可以得到消除了非正交误差的正交信号Ix'、Iy'
Ix'=RxcosφIy'=Rysinφ
因此可以得到
Ix=RxcosφIy=Rysinφcosδ+cosφsinδ=Iy'cosδ+IxRyRxsinδ
求解关于Iy'的第二个方程,得到了变换关系
Ix'=IxIy'=IyRx-IxRysinδRxcosδ
此时的正交信号Ix'和Iy'已经不存在非正交误差δ。下一步,将信号缩放到单位幅度,对其进行归一化处理后,就可以利用反正切提取相位,获取位移值。
为了验证四路正交零差激光测长系统的测量精度和测量稳定性,搭建图6所示的实验光路,使用高精度纳米定位台P-725.4CD驱动角锥移动,并采用简仪科技的USB-532216位高速数据采集卡进行光强信号采集,采集速率为2 MHZ。根据P-725.4CD 的移动量程设置移动距离为200 µm,并利用测长模块进行位移测量,测量结果如表6所示。根据统计结果,可以计算出测量结果的平均误差为4.14 nm,均方根误差为9.02 nm,反映测量系统在全程中的综合精度水平能够稳定保持在10 nm范围内;从整体上来看激光干涉测量系统的绝对误差保持在15 nm以内。
进一步地,为了评估系统在长时间运行过程中的测量稳定性和漂移特性,在恒温实验条件下,连续4个小时运行激光测长系统并进行对应的位移测量,测量结果如图7所示,实验结果表明,在恒温实验室条件下,零差激光干涉测量系统运行四个小时产生的位移测量漂移量保持在±40 nm以内。
同时为了实现实时测量,算法采用Visual Studio平台进行编程,将数据采集卡驱动与位移计算程序集成。系统采用双线程并行架构:一个线程负责数据采集,另一个线程负责数据计算。数据采集模块持续分批采集数据,其中每一批的数据量远大于一个周期的采样点数,并通过线程安全的队列依次送入数据计算模块。计算模块同时对接收到的新数据批次进行并行处理,从而提升整体吞吐量和计算效率。为评估系统实时性,利用C++标准库的高精度计时功能,对系统的实时性能进行了量化评估。对采集模块与处理模块连续运行20次的每批次耗时数据进行统计分析,如表7所示。结果表明:采集模块处理单批数据的平均耗时为0.773 9 ms,处理模块的平均耗时为0.316 6 ms。综合两者,系统完成单批次数据从采集到解算的平均总时间约为1.09 ms,同时证明了系统具备2 ms以内的数据更新周期,能够稳定实现毫秒级的位移输出与实时响应。
尽管在Visual Studio平台下,测长系统能够实现实时测量,但受限于中央处理器(Central Processing Unit, CPU)的计算能力和资源调度,数据处理与更新速度仍然维持在毫秒级别,仍存在较大的时间延迟。为了进一步提高系统的实时性和高速运算的需求,本研究在FPGA平台上完成了激光干涉测长核心算法的硬件化实现,利用FPGA的硬件并行处理特性,将差分计算、误差校正及坐标旋转数字计算方法(Coordinate Rotation Digital Computer, CORDIC)解算等核心模块进行模块化集成,并通过流水线结构级联以确保数据吞吐的连续性。测长信号处理设计方案如图8所示,系统首先接收经ADC转换后的四路数字信号输入至FPGA数字微处理器中,对其进行差分运算、直流偏置误差、不等幅误差和非正交误差修正,将修正过后的两路信号进行相位计算、辨向判断以及位移解调,最终输出整个运动过程的位移变化情况。
根据前文所述,差分处理后的信号首先被传输至实时误差校正模块进行误差校正处理。如图9所示,误差校正模块主要分为校正参数获取和非线性误差校正两个模块,其中T1、T2为FPGA的工作周期。校正参数获取模块主要用于对差分后的干涉信号数据进行校正参数提取,即分别实时计算出两路干涉弦波的直流偏置、交流振幅值与非正交误差值,并实时更新在非线性误差校正模块中,用于校正下一个工作周期的干涉信号。
实时误差校正模块的校正参数获取如图10所示。系统在差分处理完成后,利用数字比较器对干涉信号进行实时极值检测获取校正参数即干涉信号的极值,并进行动态更新。具体过程为系统将第一个干涉周期内检测到的极大值与极小值被分别作为初始参考值存储;随后,系统在数据流的持续更新过程中,将新的输入信号与当前存储的极值进行比较:若检测到信号幅值超过当前极大值,则更新为新的极大值;若信号幅值低于当前极小值,则更新为新的极小值。通过这种极值跟踪模式,系统能够在数据流实时变化的过程中,快速计算并更新最新的校正参数。
同时为了保证误差校正模块与校正参数提取的时序稳定性,模块内部设置了基于计数器控制的先进先出(First In, First Out, FIFO)缓冲结构,对两路信号进行约一个干涉周期的延迟缓存,实现了信号对齐与稳定输出。计数器在写入与读取之间建立严格的时间控制,使延迟长度固定,保证输出信号的同步性与连续性。
接着,直交流误差校正模块根据极大值与极小值计算信号的直流偏置、交流误差和非正交误差值,并在每个工作周期内实时更新,对输入信号进行直流分量的消除与幅度归一化处理。非正交误差校正单元则对干涉信号中的附加相位所造成的非正交偏差进行补偿,使两路信号恢复到理想的正交状态。整个实时误差校正波形如图11所示。
在实时误差校正模块输出两路正交信号后,系统需对其进行相位解算,由于FPGA无法直接进行反正切运算,因此本文通过基于Xilinx提供的CORDIC IP核对正余弦信号进行实时反正切运算,从而获得每个采样点的相位值,如图12所示。该方法仅需移位与加减操作即可完成迭代计算,既降低了逻辑资源消耗,又提升了相位解算的速度和精度。本文对CORDIC IP核进行了如下配置:设置架构为并行结构,以确保在每个时钟周期均可输出相位结果;输入数据位宽设为16位定点数,其中1 bit为符号位、2 bit为整数位、13 bit为小数位;输出同样为16位定点数,格式为1 bit符号位、1 bit整数位、14 bit小数位,数据格式采用有符号小数,计算范围在-π/2,π/2之间,同时输出归一化后的反正切值。在最优流水线模式下,模块输出延迟为29个时钟周期,可在连续输入条件下实现无间断的相位流输出。
在完成相位解算后,系统需进一步提取相位差数据并实现位移的连续复原,图13为辨向和位移累加模块的流程图。首先通过寄存器打拍的方式保存上一周期相位,并在每个时钟周期内实时计算相位差。同时利用通过辨向模块检测相位突变,当检测到相位差超过设定阈值时,系统自动执行补偿,模块输出的相位差数据在同步延迟控制下触发后续累加计算。位移累加模块则对相位差数据进行实时累积,并结合光源波长参数完成位移换算。辨向以及累加模块波形图如图14所示。
整个FPGA计算模块采用流水线并行结构设计,各子模块按数据流方向级联运行,极值检测、FIFO缓存、直流交流补偿及非正交校正等运算在FPGA内部以时钟为节拍并行进行。数据在各级模块间实现边输入、边计算、边输出的连续流动,使系统能够在每个工作周期内完成极值实时更新与误差同步校正。
为进一步验证所提算法的工程可行性与实时处理性能,本文搭建了基于FPGA的硬件测试平台。系统核心架构采用Linear Technology公司的LTC2270模数转换芯片与 Xilinx Kintex UltraScale 系列的 XCKU115 FPGA 芯片,其硬件架构和实际硬件板卡分别如图15和图16所示。
实验中,为满足流式处理需求,FPGA系统主时钟与ADC采样率均设定为10 MHz。在此硬件配置下,系统的最大测量速度主要受限于ADC采样率引起的相位混叠效应。依据前文式(12)计算可知,在10 MHz采样率下,系统的理论最大测量速度上限为1.582 m/s。
上板验证的信号流向如下:纳米定位台驱动测试角锥进行200 µm的定向位移,单频激光干涉测长系统产生对应的干涉信号,干涉信号经ADC采样量化后,生成16-bit的并行数据,通过双通道低压差分信号(Low-Voltage Differential Signaling, LVDS)接口高速传输至FPGA端。系统逻辑在Vivad o开发环境下完成电路综合、布局布线及比特流生成,最终解算出位置数据,通过通用异步收发器(Universal Asynchronous Receiver, UART)串口实时上传至上位机进行显示与分析。图17同时展示了部分关键模块的电路原理图。
在此基础上,系统引入集成逻辑分析仪(Integrated Logic Analyzer, ILA),捕获并分析FPGA内部数据流及相位解算过程,验证实时处理结果。图18至图21展示了利用ILA捕获的测长模块内部关键节点实时波形。如图18所示,adc_data[0]~adc_data[3]为ADC采集的四路原始干涉信号。从时域波形中可以看出,受光路及器件特性影响,四路信号虽大致保持正交关系,但仍存在一定的非正交偏差与直交流分量。该原始数据经非线性误差校正模块处理后,生成了高精度的差分正交信号;随后经CORDIC算法解算,获得线性度良好的相位观测值,如图19所示,sin_pd2和cos_pd2为经过校正后的差分正交干涉信号,arctanx为对应的反正切值。系统对相位数据进一步执行辨向逻辑与突变检测,并将其转换为位移量进行累加。如图20中的length信号所示,在匀速运动实验条件下,解算出的位移值随时间呈严格的线性增加,且无明显抖动或丢步现象,验证了逻辑设计的正确性。为量化评估系统的计算延迟,实验在干涉信号输入端与位移数据输出端分别设置了有效信号标记位。如图21所示,当输入端i_data_valid拉高时,测长模块启动计算;经流水线处理后,输出端o_valiad拉高并输出首个有效距离值。已知系统时钟周期为10 MHz,则整个解算过程的首点计算延迟为104个时钟周期,因此计算延时为10.4 μs,后续位移数据以100 ns的间隔持续更新。结果表明,对于微米量级的完整位移过程,系统可在微秒级时间内完成数据点的实时输出,充分满足了高速精密测量的实时性要求。
由于FPGA平台通常采用定点数运算以优化资源利用率、提高处理速度并降低功耗,其数值表示范围和精度理论上低于基于浮点数的上位机仿真环境。为确保算法在硬件实现后的计算精度满足应用要求,需对FPGA的输出结果进行定量评估。将FPGA处理后的结果回传至上位机,并与上位机程序的输出结果进行对比。图22和图23是针对位移量为200 µm的PC端和FPGA测试结果对比,可以发现,两个平台所计算出的实时位移路径基本重合,对比两个平台的计算结果,得到单点的计算误差为亚纳米级。为精确量化FPGA计算误差,采用纳米定位台控制角锥反射镜进行重复定位实验。位移台以200 µm为步长重复移动15次,每次移动后采集并保存对应的干涉信号,并分别通过上位机和FPGA硬件平台进行解算。最终将两组计算结果与纳米定位台的输出位移结果进行对比,结果如表7所示。从表中结果可以看出,FPGA与上位机计算的最大偏差小于3 nm。上位机和FPGA计算结果的均方根误差分别为9.09 nm和9.16 nm,均方根误差的偏差保持在亚纳米级。由此可见,尽管FPGA实现的计算结果存在亚纳米级随机误差,但总体测量精度仍保持在10 nm量级,与上位机计算结果在统计意义上等效,表明FPGA位移解算模块在实现实时计算的同时保持了高精度测量。
本文围绕高精度、高实时性的激光干涉测长需求,提出并实现了一种基于FPGA的逐点相位差激光干涉测长系统。系统采用四路正交零差干涉光路结构,基于琼斯矩阵建立了干涉信号模型,系统分析了波片角度偏差等典型非线性因素对干涉信号的非线性误差的影响机理,并通过MATLAB仿真验证了误差模型与校正方法的有效性。在系统建模与误差分析的基础上,本文面向FPGA实时处理特性,设计了逐点相位差位移解算与误差补偿方法,通过相邻采样点相位差的连续计算与相位跳变修正,避免了传统相位细分算法对完整干涉周期的依赖,显著提升了动态测量场景下的实时性。实验结果表明,所构建的激光干涉测量系统位移测量绝对误差控制在15 nm以内,均方根误差为9.02 nm,系统统计测量精度优于10 nm。进一步地,本文在FPGA平台上完成了测长算法的硬件并行实现与加速,搭建高速ADC与FPGA构建实时测量硬件平台,通过流水线化与并行处理架构,实现了误差校正、相位解算及位移输出的实时处理。实测系统计算延迟为10.4 μs,更新周期达100 ns,FPGA解算均方根误差优于10 nm,与上位机计算偏差小于3 nm。在200 μm位移测量范围内,该系统实现了纳米级测量精度与稳定连续的实时输出,验证了所提基于FPGA的激光干涉测长系统在高精度、高实时性测量中的有效性与工程应用价值。

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doi: 10.3788/gzxb20265503.0312002
  • 接收时间:2025-11-03
  • 首发时间:2026-10-10
  • 出版时间:2026-03-25
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  • 收稿日期:2025-11-03
  • 录用日期:2025-12-31
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    1南京理工大学 电子工程与光电技术学院, 南京 210094

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