Photonic architecture for remote multi-parameter measurement and transmission of microwave signals

Yi Wang; Shuna Yang; Bo Yang; Hao Chi

doi:10.1364/OE.524135

1. Introduction

In modern radar systems, the rapid and precise identification of the position and speed of moving targets is a fundamental task [1,2]. Doppler frequency shift (DFS) and Angle of arrival (AOA) are two crucial parameters for deducing the radial velocity and orientation of moving targets. Traditional DFS and AOA measurements are implemented using electronic methods, such as [3–7]. Electronic methods often have problems such as limited bandwidth, low processing speed, and susceptibility to electromagnetic interference, due to the bottleneck in electronic devices. In the recent decade, microwave photonics has received intensive research interest and is believed to be a crucial enabler in many civil and military areas. Microwave photonics technology has been demonstrated to have extensive and potential applications in various fields such as the transmission, distribution, processing, measurement, generation, reception and conversion of microwave signals, which has the advantages of large instantaneous bandwidth, low insertion loss, and immunity to electromagnetic interference [8,9]. Successive applications include radio over fiber, microwave photonic radars, optically controlled phased array antennas, microwave photonic channelizers, opto-electronic oscillators, and so on [10–13]. On the other hand, in military applications of radar systems, there is often a need to spatially separate the antenna unit and the processing unit to enable antenna remoting or reduce the risk of the processing unit. Radio over fiber technology offers a cost-effective and flexible solution for achieving long-haul transmission of radar signals. Hence, there is a significant need to develop a microwave photonic system capable of facilitating the transmission and remote multi-parameter measurement of microwave signals.

So far, a number of microwave photonic schemes for measuring DFS or AOA have been reported. In general, DFS measurement includes the DFS value measurement and the determination of direction (positive or negative radial velocity). The DFS value measurement can be realized based on the beating of the transmitted signal and echo signal or using a multi-wavelength light source [14–17]. The DFS direction determination can be realized by introducing a frequency shift module or a reference signal with a frequency deviation from the transmitted signal [18–20]. The frequency shift can be realized by using serrodyne modulation or acousto-optic modulation [21–25]. On the other hand, the estimation of AOA can be realized by measuring the phase difference of the echo signals received by two antennas spatially separated. The measurement of phase difference can be converted into the measurement of output optical power [26] or output electrical power, including the power of intermediate frequency (IF) signals [27] and DC voltage [28], based on the coherent superposition of two optical signals. Meanwhile, the measurement of AOA can also be directly implemented by constructing two optical channels and comparing the phase difference between the two IF signals carried by these channels [29].

The above schemes can only measure one parameter, i.e., DFS or AOA. In recent years, some microwave photonic schemes have been proposed for simultaneously measuring DFS and AOA. In [30], the authors proposed a photonic system with two channels, in which each channel was modulated by the echo signal from one of the two antennas and an additional reference signal was introduced in one channel. In the system, a dual-parallel MZM and a wavelength-division multiplexer (WDM) were employed to separate the modulated sidebands into two channels. However, the use of WDM limits the operational spectral range of the system. In [31–33], the authors constructed two polarized optical paths and analyzed two IF electrical signals, which were generated in the two paths for deducing the DFS and AOA information. In [31,32], the DFS value was obtained by analyzing one of the IF signals, and the AOA and direction of DFS can be obtained from the phase difference between the two IF signals. In [33], the direction and value of DFS can be directly obtained from the frequency of the IF signals due to the introduction of reference signals, and the information of AOA can be obtained by analyzing and comparing the power of two IF signals. However, the use of polarization multiplexing technology, as well as the polarization state adjusting, increases the complexity and reduces the stability of the system.

In this paper, a novel microwave photonic architecture for long-distance transmission and remote multi-parameter measurement of microwave signals is proposed and demonstrated, where the parameters include DFS, AOA, and frequency. The proposed approach is based on the use of a dual-parallel dual-drive Mach-Zehnder modulator (DP-DDMZM) and a dual-drive Mach-Zehnder modulator (DDMZM). In the system, two echo signals from two spatially separated antennas are injected to the upper and lower sub-MZMs within the DP-DDMZM, respectively, for realizing optical single sideband (OSSB) modulation, with the help of 90° electric hybrid couplers. After the modulated optical signal propagates through a length of fiber, a reference signal is applied to the following DDMZM, which is also used to achieve OSSB modulation. A beating signal between the sidebands of the modulated echo signal and the reference signal can be obtained. The DFS and AOA information can be deduced from the frequency value and power of the beating signal. The proposed scheme eliminates the need for optical filters and polarization-related devices, thereby reducing system complexity while enhancing measurement bandwidth and stability. Due to the use of OSSB, the proposed approach can effectively mitigate the frequency-dependent RF power fading caused by chromatic dispersion in optical fiber and therefore is suitable for the scenarios requiring long-distance transmission. In the experiment, high-precision simultaneous DFS (both value and direction) and AOA measurement in the X band were successfully demonstrated. Additionally, verification of long-distance microwave signal transmission without dispersion-induced power fading was provided, along with a discussion on instantaneous frequency measurement using the architecture.

2. Principle

Schematic diagram of the proposed architecture for microwave signal transmission and remote multi-parameter measurement is illustrated in Fig. 1, which comprises an antenna unit and a processing unit connected via an optical fiber. The antenna unit consists of a continuous-wave light source and a DP-DDMZM, while the processing unit comprises a measurement branch (with a DDMZM) and a transmission branch. In the antenna unit, the RF echo signals from two antennas are injected into the upper and lower sub-MZMs within the DP-DDMZM, respectively, for performing OSSB modulation through 90° electrical hybrid coupler. Then modulated optical signal is transmitted to the processing unit through the optical fiber. In the transmission branch within the processing unit, the optical signal is directly detected by a PD to receive microwave signals. In the measurement branch, a reference microwave signal is applied to the two electrodes within the DDMZM. One of the injected signals is 90° phase shifted in advance via a hybrid coupler. The optical signal is detected by a PD and an IF signal carrying the parameters information can be obtained from the PD output.

Fig. 1. The structure diagram of the proposed approach for DFS and AOA measurement. AU: antenna unit; PU: processing unit; CW: continuous-wave laser diode; DP-DDMZM: dual parallel dual drive Mach-Zehnder modulator; DDMZM: dual drive Mach-Zehnder modulator; SMF: single mode fiber; PD: photodetector.

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In the given system, the reference signal and the echo signals received by the antenna can be given as

(1)$$\begin{array}{c} {V_{ref}}(t) = {V_r}\cos ({\omega _r}t)\\ {V_{echo1}}(t) = {V_e}\cos ({\omega _e}t)\\ {V_{echo2}}(t) = {V_e}\cos ({\omega _e}t + \theta ) \end{array}$$

where ${\omega _r}$ and ${\omega _e}$ are the angular frequency of the reference and echo signals, respectively, ${V_r}$ and ${V_e}$ are the amplitude of the reference and echo signals, respectively. $\theta$ is the phase difference between the signals from two antennas, which is related to the antenna spacing and AOA [34]. Figures 2(a) and (b) show the measurement branch optical spectra at the output of the DP-DDMZM and the DDMZM, respectively. It is seen that the spectrum at the output of DP-DDMZM consists of an optical carrier ${\omega _0}$ and the coherent superposition of two first-order sidebands ${\omega _0} + {\omega _e}$ with different phases. Multiple parameters of the injected echo signal, including AOA, DFS, and frequency can be obtained from the spectrum of the output signal in the measurement branch within the processing unit. The amplitude of the first-order sideband is determined by the phase difference between the two echo signals, which can be used to deduce AOA. The frequency offset between the reference signal and the transmitted signal can be set to be, for instance, 100 MHz. The frequency of the down-converted signal with a frequency of ${\omega _r} - {\omega _e}$, after photodetection, varies from 99 MHz to 101 MHz, which can be used to distinguish both the value and direction of DFS.

Fig. 2. Optical spectra at the output of DP-DDMZM (a) and DDMZM (b).

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The continuous-wave light from the laser diode is injected into the DP-DDMZM and equally divided into two branches within the modulator. Each of the two echo signals passes through a 90° hybrid coupler prior to be injected into the sub-MZM within the DP-DDMZM, in order to realize OSSB modulation. The sub-MZMs are both biased at the quadrature points. The main modulator of the DP-DDMZM is biased at the maximum point. The optical signal at the output of the DP-DDMZM can be described as:

(2)$$\begin{array}{c} {E_1}(t) = \frac{1}{4}{E_0}\exp (j{\omega _0}t) \times \{\exp [j{\beta _e}\cos ({\omega _e}t)] + \exp [j{\beta _e}\sin ({\omega _e}t))\exp (j\frac{\pi }{2})]\\ \textrm{ } + \exp [j{\beta _e}\cos ({\omega _e}t + \theta )] + \exp [j{\beta _e}\sin ({\omega _e}t + \theta )\exp (j\frac{\pi }{2})]\} \\ = \frac{1}{4}{E_0}{e^{j{\omega _0}t}} \times [{(2 + 2j){J_0}({\beta_e}) + 2j{J_1}({\beta_e})\exp (j{\omega_e}t) + 2j{J_1}({\beta_e})\exp (j{\omega_e}t + \theta )} ]\end{array}$$

where ${E_0}$ and ${\omega _0}$ are the amplitude and angular frequency of optical carrier, $\beta e = \pi Ve/V\pi$ denote the modulation index of the echo signals, ${V_\pi }$ is the half-wave voltage of the DP-DDMZM, and ${J_n}({\cdot} )$ represents the Bessel function of the first kind with an order n. Considering the limited modulation index, the higher order Bessel functions are ignored.

The output signal from the DP-DDMZM is injected into the DDMZM in the processing unit after transmission through a coil of SMF, in which the reference signal is OSSB modulated with the help of another 90° hybrid coupler. The output optical signal from the DDMZM can be expressed as

(3)$$\begin{array}{c} {E_2}(t) = {E_1}(t) \times [\exp (j{\beta _r}\cos ({\omega _r}t)) + \exp (j{\beta _r}\sin ({\omega _r}t))\exp (j\frac{\pi }{2})]\\ = \frac{1}{4}{E_0}\exp (j{\omega _0}t) \times [4j{J_0}({\beta _e}){J_0}({\beta _r}) + (2j - 2){J_0}({\beta _e}){J_1}({\beta _r})\exp (j{\omega _r}t)\\ \textrm{ } + (2j - 2){J_1}({\beta _e}){J_0}({\beta _r})\exp (j{\omega _e}t) + (2j - 2){J_1}({\beta _e}){J_0}({\beta _r})\exp (j{\omega _e}t + \theta )\\ \textrm{ } - 4{J_1}({\beta _e}){J_1}({\beta _r})\exp (j{\omega _e}t + j{\omega _r}t) - 4{J_1}({\beta _e}){J_1}({\beta _r})\exp (j{\omega _e}t + j{\omega _r}t + \theta )] \end{array}$$

where $\beta r = \pi Vr/V\pi$ denotes the modulation index of the reference signal. According to Eq. (3) and Fig. 2(b), the spectral components of the detected signal include the RF components ${\omega _r}$ and ${\omega _e}$, as well as the IF component ${\omega _r} - {\omega _e}$. By properly choosing the reference signal, we can ensure ${\omega _e},\textrm{ }{\omega _r} > > {\omega _r} - {\omega _e}$. Therefore, if a low-speed PD with reasonable bandwidth is applied, the detected signal can only contain the down-converted IF signal, which is as

(4)$$I(t) \propto \frac{1}{2}\Re {P_0}{J_0}({\beta _e}){J_0}({\beta _r}){J_1}({\beta _e}){J_1}({\beta _r}) \times [\cos ({\omega _r}t - {\omega _e}t) + \cos ({\omega _r}t - {\omega _e}t - \theta )]$$

where $\Re$ is the responsivity of the PD, and ${P_0}$ is the optical power. For the measurement of AOA, the power of the output IF signal can be estimated according to the Eq. (4), which is expressed as

(5)$$P = \frac{1}{4}{\Re ^2}P_0^2J_0^2({\beta _e})J_0^2({\beta _r})J_1^2({\beta _e})J_1^2({\beta _r}) \times [1 + \cos (\theta )]$$

The phase difference $\theta $ can be figured out from the power of the output IF signal and therefore the AOA can be deduced. If the DFS value ranges from −1 MHz to 1 MHz, the frequency of the IF signal varies between 99 MHz and 101 MHz due to the 100 MHz frequency offset between the transmitted and reference signals. When the frequency of the IF signal falls between 99 MHz and 100 MHz, the DFS is positive (indicating that the object is moving toward the antennas). Conversely, if the frequency of the IF signal falls between 100 MHz and 101 MHz, the DFS is negative (suggesting that the object is moving away from the antennas). Therefore, both the value and direction of the DFS can be deduced from the frequency of the obtained IF signal.

In addition, the frequency of the received signal can be inferred from the frequency of the IF signal by selecting an appropriate reference signal frequency ${\omega _r}$, given that the frequency range of the signal to be measured is known. For example, if the frequency range of the received signal ${\omega _e}$ is between 10 GHz-15 GHz, the frequency of the reference signal ${\omega _r}$ can be set to 10 GHz. In this case, the frequency of the IF signal varies between 0-5 GHz. Therefore, the absolute frequency of the received signal can be inferred from the frequency of the IF signal.

The optical signal after dispersive transmission in the transmission branch within the processing unit can be expressed as

(6)$$\begin{array}{c} {E_3}(t) = \frac{1}{4}{E_0}{e^{j{\omega _0}t}} \times [(2 + 2j){J_0}({\beta _e})\exp (j{\theta _0}) + 2j{J_1}({\beta _e})\exp (j{\omega _e}t)\exp (j{\theta _1})\\ + 2j{J_1}({\beta _e})\exp (j{\omega _e}t + \theta )\exp (j{\theta _1})] \end{array}$$

where ${\theta _0}$ and ${\theta _1}$ are the dispersion-induced phase shifts of the carrier and upper sideband, respectively. Therefore, after O/E conversion at the PD, the received electric signal can be detected at the processing unit, which is as

(7)$${I_r}(t) \propto {J_0}({\beta _e}){J_1}({\beta _e})\cos (\frac{\theta }{2})\cos ({\omega _e}t - {\theta _0} + {\theta _1} + \frac{\theta }{2})$$

It is seen that due to the use of OSSB in the system, the received microwave signal can effectively avoid the frequency-dependent RF power fading caused by chromatic dispersion in optical fiber [35]. Therefore, the proposed architecture is suitable for the scenarios with separated antenna and processing units connected by long optical fiber.

3. Experiment and results

An experiment with a setup shown in Fig. 3 was conducted to validate the proposed architecture for microwave signal transmission and multi-parameter measurement. A continuous-wave light from a laser diode (ID Photonics DX2) at 1550 nm with an output power of 10 dBm was injected into a DP-DDMZM (FTM7960EX/301). The echo signals from two antennas were emulated from two synchronized microwave signal generators (R&S SMB100A and Ceyear 1435F) with adjustable phase difference. The first echo signal, with a power of 0 dBm, was directed to the upper sub-MZM within the DP-DDMZM via a 90° hybrid coupler, while the second echo signal, also with the same power but a different phase, was routed to the lower sub-MZM through another 90° hybrid coupler. The output signal from the DP-DDMZM, after transmission through a coil of SMF, is amplified by an erbium-doped fiber amplifier (AMONICS AEDFA-23-B-FA). In the measurement branch, the subsequent component was a DDMZM (FTM7937EZ/202), which was fed by a reference signal (0 dBm) from a vector network analyzer (R&S ZNB40, functioning as a microwave signal generator) via a 90° hybrid coupler to achieve OSSB modulation. The optical spectra after the DP-DDMZM and the DDMZM, recorded by an optical spectrum analyzer (Yokogawa AQ6370D) with a resolution of 0.02 nm, are shown in Figs. 4(a) and (b), respectively. A polarization controller was placed before the DP-DDMZM and the DDMZM to minimize polarization-dependent loss. The output optical signal in each branch within the processing unit was detected by a PD (Optilab, PD-40-M), and the output electrical signal was connected to an electrical spectrum analyzer (R&S FSV 30) to observe the frequency and power of the detected signal.

Fig. 3. Experimental setup. PC: polarization controller; MSG: microwave signal generator; EDFA: erbium doped fiber amplifier; ESA: electrical spectrum analyzer.

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Fig. 4. Optical spectra at the outputs of DP-DDMZM (a) and DDMZM (b).

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In the first phase of the experiment, we evaluated the capability of the approach to measure multiple parameters, encompassing the direction and value of DFS and AOA. Specifically, we initially verified the approach's ability to discern the direction of DFS in the initial demonstration. The frequency of the transmitted signal was assumed to be 10 GHz and the DFS was assumed to be +1 MHz and -1 MHz. The frequency of the reference signal was set to 10.1 GHz. Figures 5(a) and (b) depict the spectra of the down-converted IF signals corresponding to the DFS of +1 MHz and -1 MHz, respectively. The spectral components of 101 MHz and 99 MHz are clearly seen for the two cases, which can unambiguously distinguish the direction of DFS and determine the value of DFS based on ${\omega _{IF}} - {\omega _{OS}}$.

Fig. 5. Recorded spectra for the echo signals of 10 GHz-1 MHz (a) and 10 GHz + 1 MHz (b), respectively.

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Next, the DFS value measurement in a wide range was tested. For this, the frequencies of the transmitted signal and the reference signal were kept at 10 GHz and 10.1 GHz, respectively. The phase difference between the two injected signals was fixed, but the DFS was varied from -100 kHz to +100 kHz at a 10 kHz step. The measurement result without 20-km SMF is shown in Fig. 6(a), where the measurement errors are kept within 2 Hz. Then, the 20-km SMF was added and the measurement result is given in Fig. 6(b), in which the measurement errors are also within 2 Hz. The experimental results demonstrate that the system can achieve remote DFS measurement with high accuracy.

Fig. 6. Measured DFS (blue square) and corresponding errors (red circle) for the DFS varied from −100 kHz to 100 kHz with a step of 10 kHz, without (a) and with (b) 20 km SMF at the frequency of 10 GHz.

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To further demonstrate the capability for DFS measurement within a wide frequency range, the frequency of the echo signal was changed from 5 GHz ± 100 kHz at a 10 kHz step and 15 GHz ± 100 kHz at a 10 kHz step, respectively. After 20-km fiber transmission, the corresponding reference signals were set to 5.1 GHz and 15.1 GHz, respectively. The peak frequency was measured on the ESA with a setting of 20 Hz resolution bandwidth and 300 kHz span. Figures 7(a) and (b) show that the DFS measurement errors are less than 2 Hz. The experimental results demonstrate that the system is suitable for the DFS measurement with a wide frequency range.

Fig. 7. DFS measurement results for the echo signals at 5 GHz (a) and 15 GHz (b).

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To test the stability of the system with 20-km fiber transmission, we conducted DFS measurements over a period of 60 minutes. The frequencies of the echo and reference signals were set to be 10 GHz and 10.1 GHz, respectively. Results are shown in Fig. 8. It is observed the frequency fluctuation of the measured DFS remains within 0.2 Hz, corresponding to a radial velocity error of less than 0.003 m/s. It indicates that the DFS measurement has good system stability.

Fig. 8. DFS Measurement results over 60 minutes.

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We investigated the AOA measurement of the proposed system in the next step. In order to evaluate the AOA measurement performance, the frequencies of the echo signals and reference signal were set to be 10 GHz and 10.1 GHz, respectively. We adjusted the phase difference between the two injected signals from 0 to 180 degrees via the employed signal generators. In AOA measurement, the phase difference between two echo signals varies from 0 degrees to 180 degrees in a step of 10 degrees to simulate the phase difference between the signals from two antennas. Powers of the down-converted IF signals corresponding to 19 phase differences were recorded. The dependence of the normalized power on the phase difference is shown in Fig. 9(a). For comparison, both the measured and theoretical results are given and perfect agreement between them is observed. Figure 9(b) shows the AOA measurement results and the corresponding measurement errors. The given results show that the AOA measurement error is within 2° errors in the range of 12.84° to 90°. However, the measurement error increases significantly when the AOA is less than 10°, which can be attributed to the flat slope observed in the curve of power versus phase difference for small AOAs.

Fig. 9. (a) Measured (red circle) and theoretical (solid line) normalized power versus phase difference. (b) Estimated AOA versus actual AOA (blue square) and measurement errors (red inverted triangle).

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In the final step of the experiment, we evaluated the transmission performance for the injected RF signals with a long dispersive fiber connected between the antenna unit and the processing unit. For this, the frequency of the injected signal was varied from 2 GHz to 20 GHz at a 1 GHz step. The output RF signals were observed by a spectrum analyzer and the RF powers were recorded. For comparison, the same experiment but with optical double sideband modulation was carried out and the output RF powers were recorded. The experimental results are shown in Fig. 10. It is evident that the RF power fading phenomenon induced by chromatic dispersion is eliminated in our approach due to the use of optical single sideband modulation. The dispersion-induced power fading is undesired in radio over fiber since it would result in power nulls at certain frequencies for a given chromatic dispersion value. Therefore, the proposed architecture can be employed for antenna remoting, enabling not only multi-parameter measurement based on the information in IF signals but also long-distance transmission of RF signals.

Fig. 10. Normalized RF power versus frequency in the given approach (blue circle) (a) and the system with ODSB modulation (red square) (b).

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We have demonstrated the ability of the approach for remote multi-parameter measurement as well as transmission of microwave signals. One concern regarding performance is on the stability of the system, which may be influenced by the temperature drift of the applied modulators. To enhance stability of the system, we can employ dc bias control circuits to lock onto desired bias points of the modulators. Another issue relates to weak echo signals, as they can degrade the signal-to-noise ratio (SNR) of the output IF signals. To address this, a pre-processing module can be incorporated before injecting the echo signals into the photonic system. This module amplifies the signals and stabilizes the signals at a consistent power level. As a result, the measurement can be independent of the power of the input echo signals due to this pre-processing step. We have demonstrated that the function of the RF signal transmission is immune to the dispersion-induced frequency-dependent power fading. In fact, thanks to the use of single sideband modulation, the DFS and AOA measurement functions remain unaffected by the dispersion-induced degradation. This immunity to dispersion effects is highly desirable in practical applications.

4. Conclusion

In summary, a novel photonic architecture for microwave signal transmission and multi-parameter measurement has been presented and experimentally demonstrated, which utilizes a DP-DDMZM in the antenna unit and a DDMZM in the processing unit. Due to the introduction of reference signals in the processing unit, the absolute value and direction of DFS can be determined based on the information in the obtained IF signals. We have successfully demonstrated the accurate DFS and AOA measurement for signals within 5 GHz to 15 GHz, in which measurement errors were kept within 2 Hz in the range of ±100 kHz for DFS measurement and 2° in the range of 12.84° to 90° for AOA measurement. We also discussed the feasibility for instantaneous frequency measurement based on down-conversion using the same architecture. Due to the use of optical single-band modulation, the long-distance transmission of RF signals without dispersion-induced RF power fading problem can be achieved. In addition, the proposed system does not involve the use of filters or polarization-related devices, which enables a wide operating bandwidth and ensures good stability. We believe the proposed architecture is a promising candidate for microwave photonic antenna remoting, supporting both multi-parameter measurement and long-distance transmission.

Funding

National Natural Science Foundation of China (62375071, 62101168); Natural Science Foundation of Zhejiang Province (LY22F050010).

Disclosures

The authors declare no conflicts of interest.

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

References

1. V. C. Chen, F. Li, S.-S. Ho, et al., “Micro-Doppler effect in radar: phenomenon, model, and simulation study,” IEEE Trans. Aerosp. Electron. Syst. 42(1), 2–21 (2006). [CrossRef]

2. J. Hasch, E. Topak, R. Schnabel, et al., “Millimeter-wave technology for automotive radar sensors in the 77 GHz frequency band,” IEEE Trans. Microwave Theory Techn. 60(3), 845–860 (2012). [CrossRef]

3. T. Sakamoto, A. Matsuoka, and H. Yomo, “Estimation of Doppler velocities from sub-Nyquist ultra-wideband radar measurements,” IEEE Sensors J. 16(23), 1 (2016). [CrossRef]

4. K. Thurn, D. Shmakov, G. Li, et al., “Concept and implementation of a PLL-controlled interlaced chirp sequence radar for optimized range Doppler measurements,” IEEE Trans. Microwave Theory Techn. 64(10), 3280–3289 (2016). [CrossRef]

5. C. A. Gómez-Vega, J. Cardenas, J. C. Ornelas-Lizcano, et al., “Doppler spectrum measurement platform for narrowband V2 V channels,” IEEE Access 10(1), 27162–27184 (2022). [CrossRef]

6. M. Malajner, D. Gleich, and P. Planinšič, “Angle of arrival measurement using multiple static monopole antennas,” IEEE Sensors J. 15(6), 3328–3337 (2015). [CrossRef]

7. A. Zandamela, A. Chiumento, N. Marchetti, et al., “Exploiting multimode antennas for MIMO and AOA estimation in Size-Constrained IoT devices,” IEEE Sens. Lett. 7(3), 1–4 (2023). [CrossRef]

8. J. Yao, “Microwave Photonics,” J. Lightwave Technol. 27(3), 314–335 (2009). [CrossRef]

9. J. Capmany and D. Novak, “Microwave photonics combines two worlds,” Nat. Photonics. 1(6), 319–330 (2007). [CrossRef]

10. N. Pleros, K. Vyrsokinos, K. Tsagkaris, et al., “A 60 GHz Radio-Over-Fiber network architecture for seamless communication with high mobility,” J. Lightwave Technol. 27(12), 1957–1967 (2009). [CrossRef]

11. S. Pan, X. Ye, Y. Zhang, et al., “Microwave photonic array radars,” IEEE J. Microw. 1(1), 176–190 (2021). [CrossRef]

12. X. Zou, W. Li, W. Pan, et al., “Photonic-Assisted microwave channelizer with improved channel characteristics based on Spectrum-Controlled stimulated Brillouin scattering,” IEEE Trans. Microwave Theory Techn. 61(9), 3470–3478 (2013). [CrossRef]

13. D. Eliyahu, W. Liang, E. Dale, et al., “Resonant widely tunable Opto-Electronic oscillator,” IEEE Photon. Technol. Lett. 25(15), 1535–1538 (2013). [CrossRef]

14. X. Zou, B. Lu, W. Pan, et al., “Photonics for microwave measurements,” Laser Photon. Rev. 10(5), 711–734 (2016). [CrossRef]

15. X. Zou, W. Li, B. Lu, et al., “Photonic approach to wide-frequency-range high-resolution microwave/millimeter-wave Doppler frequency shift estimation,” IEEE Trans. Microwave Theory Techn. 63(4), 1421–1430 (2015). [CrossRef]

16. H. Emami, M. Hajihashemi, and S. E. Alavi, “Standalone microwave photonics Doppler shift estimation system,” J. Lightwave Technol. 34(15), 3596–3602 (2016). [CrossRef]

17. H. Emami, M. Hajihashemi, and S. E. Alavi, “Improved sensitivity RF photonics Doppler frequency measurement system,” IEEE Photonics J. 8(5), 1–8 (2016). [CrossRef]

18. C. Huang, E. H. W. Chan, and C. B. Albert, “Wideband DFS measurement using a low-frequency reference signal,” IEEE Photon. Technol. Lett. 31(20), 1643–1646 (2019). [CrossRef]

19. P. Zuo and Y. Chen, “Photonic-assisted filter-free microwave Doppler frequency shift measurement using a fixed low-frequency reference signal,” J. Lightwave Technol. 38(16), 4333–4340 (2020). [CrossRef]

20. J. Li, W. Yu, Z. Zhang, et al., “Simple approach for Doppler frequency shift estimation based on a dual-polarization quadrature phase shift keying (DP-QPSK) modulator,” Appl. Opt. 59(7), 2114–2120 (2020). [CrossRef]

21. B. Lu, W. Pan, X. Zou, et al., “Wideband Doppler frequency shift measurement and direction ambiguity resolution using optical frequency shift and optical heterodyning,” Opt. Lett. 40(10), 2321–2324 (2015). [CrossRef]

22. C. Yi, H. Chi, B. Yang, et al., “A PM-based approach for Doppler frequency shift measurement and direction discrimination,” Opt. Commun. 458, 124796 (2020). [CrossRef]

23. L. M. Johnson and C. H. Cox, “Serrodyne optical frequency translation with high sideband suppression,” J. Lightwave Technol. 6(1), 109–112 (1988). [CrossRef]

24. C. Huang and E. H. W. Chan, “All-optical pulsed signal Doppler frequency shift measurement system,” IEEE Photonics J. 13(6), 1–7 (2021). [CrossRef]

25. Y. Chen and T. Shi, “Simplified Doppler frequency shift measurement enabled by serrodyne optical frequency translation,” IEEE Microw. Wireless Compon. Lett. 32(5), 452–455 (2022). [CrossRef]

26. Z. Cao, H. P. A. van den Boom, R. Lu, et al., “Angle-of-arrival measurement of a microwave signal using parallel optical delay detector,” IEEE Photon. Technol. Lett. 25(19), 1932–1935 (2013). [CrossRef]

27. H. Chen and E. H. W. Chan, “Photonics-based CW/pulsed microwave signal AOA measurement system,” J. Lightwave Technol. 38(8), 2292–2298 (2020). [CrossRef]

28. H. Chen and E. H. W. Chan, “Simple Approach to Measure Angle of Arrival of a Microwave Signal,” IEEE Photon. Technol. Lett. 31(22), 1795–1798 (2019). [CrossRef]

29. C. Huang and E. H. W. Chan, “Photonic frequency down conversion approach to measure microwave signal angle of arrival,” IEEE Photonics J. 14(3), 1–8 (2022). [CrossRef]

30. H. Zhuo and A. Wen, “A photonic approach for Doppler-frequency-shift and angle-of-arrival measurement without direction ambiguity,” J. Lightwave Technol. 39(6), 1688–1695 (2021). [CrossRef]

31. P. Li, L. Yan, J. Ye, et al., “Photonic approach for simultaneous measurements of Doppler frequency-shift and angle-of-arrival of microwave signals,” Opt. Express 27(6), 8709–8716 (2019). [CrossRef]

32. J. Zhao, Z. Tang, and S. Pan, “Photonic approach for simultaneous measurement of microwave DFS and AOA,” Appl. Opt. 60(16), 4622–4626 (2021). [CrossRef]

33. X. H. Cao, X. J. Fan, G. Y. Li, et al., “A filterless photonic Approach for DFS and AOA measurement using a push-pull DPol-MZM,” IEEE Photon. Technol. Lett. 34(1), 19–22 (2022). [CrossRef]

34. A. Arafa, S. Dalmiya, R. Klukas, et al., “Angle-of-arrival reception for optical wireless location technology,” Opt. Express 23(6), 7755–7766 (2015). [CrossRef]

35. J. L. Corral, J. Marti, and J. M. Fuster, “General expressions for IM/DD dispersive analog optical links with external modulation or optical up- conversion in a Mach–Zehnder electrooptical modulator,” IEEE Trans. Microwave Theory Techn. 49(10), 1968–1976 (2001). [CrossRef]

Photonic architecture for remote multi-parameter measurement and transmission of microwave signals

Abstract

1. Introduction

2. Principle

3. Experiment and results

4. Conclusion

Funding

Disclosures

Data availability

References

Data availability

Cited By

Figures (10)

Equations (7)

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