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This article presents experimental results of target detection using a miniaturized multichannel passive radar system that exploits Long Term Evolution (LTE) signals. First, the advantages of LTE signals are discussed with respect to their ambiguity function. Second, both system design and field experiments are introduced. Finally, agreements between different targets and their truth obtained in the results prove the technical feasibility of using LTE signals for detecting ground and low-altitude targets via field experiments, thus forming the basis for further development of LTE-based passive radar. This article presents experimental results of target detection using a miniaturized multichannel passive radar system that exploits Long Term Evolution (LTE) signals. First, the advantages of LTE signals are discussed with respect to their ambiguity function. Second, both system design and field experiments are introduced. Finally, agreements between different targets and their truth obtained in the results prove the technical feasibility of using LTE signals for detecting ground and low-altitude targets via field experiments, thus forming the basis for further development of LTE-based passive radar.
In the study of the terrain classification based on the Polarimetric Synthetic Aperture Radar (PolSAR), the algorithms based on general CNN do not fully utilize the phase information in different channels, and the pixel-by-pixel classification strategy with extensive redundant computation is inefficient. To mitigate these problems, a deep pixel-to-pixel mapping model in the complex domain is used for achieving a fast and accurate PolSAR terrain classification at a low sampling rate. To completely utilize the phase information, this study uses Group-Cross CNN to extend the original model to the complex domain allowing complex-number input signals and significantly improving the classification accuracy. In addition, to speed up the algorithm, a Fine-tuned Dilated Group-Cross CNN (FDGC-CNN) was adopted to directly achieve pixel-to-pixel mapping as well as improve accuracy. We verified the adopted model on two PolSAR images comprising 16 classes terrains from the AIRSAR and 4 classes terrains from the E-SAR. According to our model, the overall classification accuracies were 96.94% and 90.07% respectively while the running time was 4.22 s and 4.02 s respectively. Therefore, FDGC-CNN achieved better accuracy with higher efficiency compared to SVM and traditional CNN. In the study of the terrain classification based on the Polarimetric Synthetic Aperture Radar (PolSAR), the algorithms based on general CNN do not fully utilize the phase information in different channels, and the pixel-by-pixel classification strategy with extensive redundant computation is inefficient. To mitigate these problems, a deep pixel-to-pixel mapping model in the complex domain is used for achieving a fast and accurate PolSAR terrain classification at a low sampling rate. To completely utilize the phase information, this study uses Group-Cross CNN to extend the original model to the complex domain allowing complex-number input signals and significantly improving the classification accuracy. In addition, to speed up the algorithm, a Fine-tuned Dilated Group-Cross CNN (FDGC-CNN) was adopted to directly achieve pixel-to-pixel mapping as well as improve accuracy. We verified the adopted model on two PolSAR images comprising 16 classes terrains from the AIRSAR and 4 classes terrains from the E-SAR. According to our model, the overall classification accuracies were 96.94% and 90.07% respectively while the running time was 4.22 s and 4.02 s respectively. Therefore, FDGC-CNN achieved better accuracy with higher efficiency compared to SVM and traditional CNN.
According to the different concentration levels of Doppler spectrum between sea clutter and target, small target in sea clutter background can be detected using Shannon entropy. However, Shannon entropy is merely a special case of Tsallis entropy and cannot reflect the multifractality of sea clutter. In this paper, the relation between Tsallis entropy and the generalized fractal dimension is first presented, and then the Doppler spectrum’s concentrative level and multifractality of sea clutter are combined; finally an algorithm for detecting small target in sea clutter background based on Tsallis entropy of Doppler spectrum rather than of Shannon entropy is proposed. By comparison via IPIX dataset, the detection’s performance of Tsallis entropy is better than that of Shannon entropy and Hurst exponent as per short observations. According to the different concentration levels of Doppler spectrum between sea clutter and target, small target in sea clutter background can be detected using Shannon entropy. However, Shannon entropy is merely a special case of Tsallis entropy and cannot reflect the multifractality of sea clutter. In this paper, the relation between Tsallis entropy and the generalized fractal dimension is first presented, and then the Doppler spectrum’s concentrative level and multifractality of sea clutter are combined; finally an algorithm for detecting small target in sea clutter background based on Tsallis entropy of Doppler spectrum rather than of Shannon entropy is proposed. By comparison via IPIX dataset, the detection’s performance of Tsallis entropy is better than that of Shannon entropy and Hurst exponent as per short observations.
In multichannel Synthetic Aperture Radar (SAR) data processing, the phase and amplitude characteristics of all channels should be well calibrated before multichannel data reconstruction; otherwise, the imaging result will be degraded and suffer from ghost targets. The yaw and pitch of the SAR platform, which change in azimuth and range, respectively, will cause phase mismatch among different channels. The currently developed attitude-aided phase mismatch calibration method does not consider the topographic relief. On the basis of the external Digital Elevation Model (DEM) and attitude information, a new phase mismatch calibration method is proposed in this study. The proposed method performs better than other methods in mountainous areas. A simulation experiment and the corresponding quantitative assessment are conducted. Then, the newly proposed method is applied to airborne multichannel SAR experimental data for further verification. In multichannel Synthetic Aperture Radar (SAR) data processing, the phase and amplitude characteristics of all channels should be well calibrated before multichannel data reconstruction; otherwise, the imaging result will be degraded and suffer from ghost targets. The yaw and pitch of the SAR platform, which change in azimuth and range, respectively, will cause phase mismatch among different channels. The currently developed attitude-aided phase mismatch calibration method does not consider the topographic relief. On the basis of the external Digital Elevation Model (DEM) and attitude information, a new phase mismatch calibration method is proposed in this study. The proposed method performs better than other methods in mountainous areas. A simulation experiment and the corresponding quantitative assessment are conducted. Then, the newly proposed method is applied to airborne multichannel SAR experimental data for further verification.
To address the problem of radar High-Resolution Range Profile (HRRP) target recognition, traditional methods only consider the envelope information of the sample and ignore the temporal correlation between the range cells. In this study, we propose a bidirectional self-recurrent neural network model based on an attention mechanism. The model divides the HRRP data in the time domain into two sequences, i.e., forward and backward using a sliding window, then extracts the features through two independent GRU networks, and splices the extracted features simultaneously, thus utilizing the bidirectional temporal information of HRRP. Considering that sequences at different moments have different degrees of importance to the target classification, different attention weights are assigned to the hidden layer features at each moment. Finally, the model uses the hidden features weighted summation to obtain target recognition and classification result. Experimental results show that the proposed method can effectively solve the target recognition problem of HRRP, and that the target area can still be accurately identified when the time shift occurs. To address the problem of radar High-Resolution Range Profile (HRRP) target recognition, traditional methods only consider the envelope information of the sample and ignore the temporal correlation between the range cells. In this study, we propose a bidirectional self-recurrent neural network model based on an attention mechanism. The model divides the HRRP data in the time domain into two sequences, i.e., forward and backward using a sliding window, then extracts the features through two independent GRU networks, and splices the extracted features simultaneously, thus utilizing the bidirectional temporal information of HRRP. Considering that sequences at different moments have different degrees of importance to the target classification, different attention weights are assigned to the hidden layer features at each moment. Finally, the model uses the hidden features weighted summation to obtain target recognition and classification result. Experimental results show that the proposed method can effectively solve the target recognition problem of HRRP, and that the target area can still be accurately identified when the time shift occurs.
In complex marine environments, sea clutter greatly affects the detection performance of maritime targets. Because the influencing factors of sea clutter are numerous and the mechanism is complex, there are great difficulties in feature description and sea clutter suppression, and it is necessary to carry out long-term, systematic, continuous, and in-depth research. Carrying out sea clutter measurement experiments and obtaining measurement data under the influence of different parameters is an important prerequisite for supporting this research. This paper mainly focuses on the sea clutter measurements that have been carried out. First, typical experiments in various countries such as Canada, South Africa, Australia, the United States, Spain, and Germany are categorized and summarized from the aspects of shore-based experiment and airborne experiment. Then, sea clutter measurement experiments with wave tank conducted by the United States and Japan are reviewed, and domestic sea clutter measurement experiments as well as the construction of the maritime target detection experimental center in Yantai are briefly introduced. Finally, the future research directions that should be emphasized are projected: more systematic and continuous sea clutter measurement experiments need to be conducted; experiment and data analysis under explicit task background need to be strengthened; and sea clutter and target datasets that meet the requirement of intelligent radar applications need to be urgently constructed. In complex marine environments, sea clutter greatly affects the detection performance of maritime targets. Because the influencing factors of sea clutter are numerous and the mechanism is complex, there are great difficulties in feature description and sea clutter suppression, and it is necessary to carry out long-term, systematic, continuous, and in-depth research. Carrying out sea clutter measurement experiments and obtaining measurement data under the influence of different parameters is an important prerequisite for supporting this research. This paper mainly focuses on the sea clutter measurements that have been carried out. First, typical experiments in various countries such as Canada, South Africa, Australia, the United States, Spain, and Germany are categorized and summarized from the aspects of shore-based experiment and airborne experiment. Then, sea clutter measurement experiments with wave tank conducted by the United States and Japan are reviewed, and domestic sea clutter measurement experiments as well as the construction of the maritime target detection experimental center in Yantai are briefly introduced. Finally, the future research directions that should be emphasized are projected: more systematic and continuous sea clutter measurement experiments need to be conducted; experiment and data analysis under explicit task background need to be strengthened; and sea clutter and target datasets that meet the requirement of intelligent radar applications need to be urgently constructed.
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A distributed multi-target localization system based on optical Wavelength Division Multiplexing (WDM) network is demonstrated. The wideband orthogonal waveforms are generated by introducing the chaotic OptoElectronic Oscillator (OEO). The optical WDM network is introduced to transmit the wideband signals from multiple distributed transmitting and receiving units to the central station for processing, and the accurate localization of multiple targets is achieved based on the time of arrival localization method. The multiple optical carriers are generated at the central station, the complex processing to achieve the high-precision of the target localization is supported by the resources at the central station, and the remote transmitting and receiving units are simplified. Moreover, a proof of concept of the distributed multi-target localization system based on optical WDM network is obtained. The localization system comprising two transmitters and two receivers is experimentally established. The orthogonal chaotic waveforms with the frequency range of 3.1~10.6 GHz are successfully generated from the chaotic OEOs. The two-dimensional localization of two targets is realized via the maximum positioning error of 7.09 cm. Additionally, the reconfiguration of the system is experimentally verified. A distributed multi-target localization system based on optical Wavelength Division Multiplexing (WDM) network is demonstrated. The wideband orthogonal waveforms are generated by introducing the chaotic OptoElectronic Oscillator (OEO). The optical WDM network is introduced to transmit the wideband signals from multiple distributed transmitting and receiving units to the central station for processing, and the accurate localization of multiple targets is achieved based on the time of arrival localization method. The multiple optical carriers are generated at the central station, the complex processing to achieve the high-precision of the target localization is supported by the resources at the central station, and the remote transmitting and receiving units are simplified. Moreover, a proof of concept of the distributed multi-target localization system based on optical WDM network is obtained. The localization system comprising two transmitters and two receivers is experimentally established. The orthogonal chaotic waveforms with the frequency range of 3.1~10.6 GHz are successfully generated from the chaotic OEOs. The two-dimensional localization of two targets is realized via the maximum positioning error of 7.09 cm. Additionally, the reconfiguration of the system is experimentally verified.
Distributed Coherent Aperture Radar (DCAR) utilizes multiple separated antenna apertures to emit signals in the same space area, realizing spatial coherent synthesis of electro-magnetic waves. Such a flexible radar system has advantages such as higher resolution, greater radar power, and lower cost. Combined with microwave photonic technologies, which have merits in wideband signal generation, transmission and procession, the DCAR has a comprehensive and better performance. This paper introduces a microwave photonics-based high-resolution distributed coherent aperture radar that was proposed by researchers of Tsinghua University. Taking advantages of microwave photonic technology, a group of wideband orthogonal phase-coded linear frequency modulation waves is generated in the coherence-on-receive mode, with the frequency ranging from 8.5 GHz to 11.5 GHz, all with phase coding under a bit rate of 0.5 Gbps. The orthogonality of the signals is nearly 30 dB, and the range resolution is better than 0.05 m. While in the full coherence mode, the transmitted waveforms can be flexibly switched to the wideband coherent linear frequency modulation waves, and the full coherent synthesis can be realized. The waveforms generated by the proposed system can meet the waveform requirements of the DCAR in different operation modes. In the experiment, full coherence is achieved with two sets of radars, resulting a signal- to-noise ratio gain of 8.3 dB. Distributed Coherent Aperture Radar (DCAR) utilizes multiple separated antenna apertures to emit signals in the same space area, realizing spatial coherent synthesis of electro-magnetic waves. Such a flexible radar system has advantages such as higher resolution, greater radar power, and lower cost. Combined with microwave photonic technologies, which have merits in wideband signal generation, transmission and procession, the DCAR has a comprehensive and better performance. This paper introduces a microwave photonics-based high-resolution distributed coherent aperture radar that was proposed by researchers of Tsinghua University. Taking advantages of microwave photonic technology, a group of wideband orthogonal phase-coded linear frequency modulation waves is generated in the coherence-on-receive mode, with the frequency ranging from 8.5 GHz to 11.5 GHz, all with phase coding under a bit rate of 0.5 Gbps. The orthogonality of the signals is nearly 30 dB, and the range resolution is better than 0.05 m. While in the full coherence mode, the transmitted waveforms can be flexibly switched to the wideband coherent linear frequency modulation waves, and the full coherent synthesis can be realized. The waveforms generated by the proposed system can meet the waveform requirements of the DCAR in different operation modes. In the experiment, full coherence is achieved with two sets of radars, resulting a signal- to-noise ratio gain of 8.3 dB.
A dual-band LFM-CW radar scheme which is based on photonic stretch processing is proposed. The receiver which is based on a photonic frequency down-converter is able to receive the radar echoes of two bands with a single hardware. A dual polarization quadrature phase shift keying modulator is employed to implement the modulation scheme. The reference signals and echoes of two bands are modulated to orthogonally polarized light waves and sent to a Pol-demux coherent receiver through an amplifier and a filter, respectively, to perform stretch processing. In the transmitter, the reference and transmitted LFM signals with high frequency and wide bandwidth are generated by a photonic-assisted frequency multiplication module. Meanwhile, the generated signal is delayed before transmission. Thus, at the output of the coherent receiver, IF signals corresponding to two bands can be separated in the frequency domain. An experimental system operating in C- and Ku-bands with transmitting signal bandwidths of 1 and 2 GHz, respectively, is demonstrated and evaluated via a series of inverse synthetic aperture radar imaging tests, and the sampling rate of analog to digital converters is 100 MSa/s. The results show that the microwave photonics technology can provide solutions for receiving dual-band signal with a single hardware platform. A dual-band LFM-CW radar scheme which is based on photonic stretch processing is proposed. The receiver which is based on a photonic frequency down-converter is able to receive the radar echoes of two bands with a single hardware. A dual polarization quadrature phase shift keying modulator is employed to implement the modulation scheme. The reference signals and echoes of two bands are modulated to orthogonally polarized light waves and sent to a Pol-demux coherent receiver through an amplifier and a filter, respectively, to perform stretch processing. In the transmitter, the reference and transmitted LFM signals with high frequency and wide bandwidth are generated by a photonic-assisted frequency multiplication module. Meanwhile, the generated signal is delayed before transmission. Thus, at the output of the coherent receiver, IF signals corresponding to two bands can be separated in the frequency domain. An experimental system operating in C- and Ku-bands with transmitting signal bandwidths of 1 and 2 GHz, respectively, is demonstrated and evaluated via a series of inverse synthetic aperture radar imaging tests, and the sampling rate of analog to digital converters is 100 MSa/s. The results show that the microwave photonics technology can provide solutions for receiving dual-band signal with a single hardware platform.
In this study, we designed and demonstrated the performance of a multi-antenna remote differential monitoring system based on a single GNSS-over-fiber architecture. In this system, multiple GNSS signals are received by remote antennas through a microwave photonic link and are then transmitted to local end points. To enable fine positioning, we established a double differential model equation for use between the carrier phase of each remotely received signal and the reference GNSS signal, with the help of the time division mode using a high-speed optical switch. In our experiment, we established a 10 km microwave photonic link among three remote monitoring points. We estimate the resulting positioning accuracy to be within several millimeters and we obtained a response time of less than 10 ms. Compared with traditional single-antenna schemes, our designed system has significant advantages with respect to coverage area, real-time response time, and the performance cost of large-scale monitoring at no cost to the positioning accuracy. As such, this system will find important applications for the monitoring of large-scale civil engineering and natural environments. In this study, we designed and demonstrated the performance of a multi-antenna remote differential monitoring system based on a single GNSS-over-fiber architecture. In this system, multiple GNSS signals are received by remote antennas through a microwave photonic link and are then transmitted to local end points. To enable fine positioning, we established a double differential model equation for use between the carrier phase of each remotely received signal and the reference GNSS signal, with the help of the time division mode using a high-speed optical switch. In our experiment, we established a 10 km microwave photonic link among three remote monitoring points. We estimate the resulting positioning accuracy to be within several millimeters and we obtained a response time of less than 10 ms. Compared with traditional single-antenna schemes, our designed system has significant advantages with respect to coverage area, real-time response time, and the performance cost of large-scale monitoring at no cost to the positioning accuracy. As such, this system will find important applications for the monitoring of large-scale civil engineering and natural environments.
An ultrahigh-resolution microwave photonic-based Synthetic Aperture Radar (SAR) imaging method based on space-variant motion error analysis is proposed to solve the influence of space-variant motion error on microwave photonic-based SAR imaging. First, the judgment rules of the influence of space-variant motion error are proposed to analyze the residual space-variant motion error. Second, on the basis of the different judgment results of microwave photonic-based SAR system conditions, the corresponding imaging process is proposed. Finally, the proposed judgment rules and imaging method are verified by point simulation, and the measured data of the 10 GHz microwave photonic-based ultrahigh-resolution SAR are analyzed and imaged. The experimental results show the effectiveness of the proposed method. An ultrahigh-resolution microwave photonic-based Synthetic Aperture Radar (SAR) imaging method based on space-variant motion error analysis is proposed to solve the influence of space-variant motion error on microwave photonic-based SAR imaging. First, the judgment rules of the influence of space-variant motion error are proposed to analyze the residual space-variant motion error. Second, on the basis of the different judgment results of microwave photonic-based SAR system conditions, the corresponding imaging process is proposed. Finally, the proposed judgment rules and imaging method are verified by point simulation, and the measured data of the 10 GHz microwave photonic-based ultrahigh-resolution SAR are analyzed and imaged. The experimental results show the effectiveness of the proposed method.
Microwave photonic radars can transmit large bandwidth and high carrier frequency signals, which makes two-dimensional high-resolution Inverse Synthetic Aperture Radar (ISAR) imaging possible. It is important to study the corresponding real-time imaging algorithms. However, the high range resolution and high carrier frequency of the signal make the space curvature of the distance bend non-negligible. This is the reason for the poor imaging performance of the traditional Doppler real-time imaging algorithm. In addition, the computationally intensive beam domain imaging algorithm is not suitable for microwave photonic radar signals of large data volume. Therefore, a high-efficiency microwave photonic ISAR high-resolution real-time imaging algorithm is proposed in this paper. Firstly, this algorithm uses the Generalized Keystone Transform (GKT) to extract the phase of the special display point. Next, it inverts the target lateral velocity from phase modulation frequency. Finally, the result of velocity estimation and Frequency Scaling (FS) are used to correct the distance space-bending and conduct matched filtering imaging in azimuth. The simulation results and the measured data have been shown to verify the effectiveness of the proposed algorithm. Microwave photonic radars can transmit large bandwidth and high carrier frequency signals, which makes two-dimensional high-resolution Inverse Synthetic Aperture Radar (ISAR) imaging possible. It is important to study the corresponding real-time imaging algorithms. However, the high range resolution and high carrier frequency of the signal make the space curvature of the distance bend non-negligible. This is the reason for the poor imaging performance of the traditional Doppler real-time imaging algorithm. In addition, the computationally intensive beam domain imaging algorithm is not suitable for microwave photonic radar signals of large data volume. Therefore, a high-efficiency microwave photonic ISAR high-resolution real-time imaging algorithm is proposed in this paper. Firstly, this algorithm uses the Generalized Keystone Transform (GKT) to extract the phase of the special display point. Next, it inverts the target lateral velocity from phase modulation frequency. Finally, the result of velocity estimation and Frequency Scaling (FS) are used to correct the distance space-bending and conduct matched filtering imaging in azimuth. The simulation results and the measured data have been shown to verify the effectiveness of the proposed algorithm.
We propose a novel scheme of broadband LFM radar imaging system based on microwave photonic I/Q de-chirping. In the transmitter, a broadband linear frequency modulated signal is generated by photonic frequency-doubling. In the receiver, echoes reflected from the target are simultaneously sent to a couple of modulators in two polarization states. After the bias voltage of the corresponding modulator is adjusted to introduce a 90° phase difference, photonic I/Q de-chirping reception of radar echoes is achieved. The proposed radar is capable of real-time high-resolution detection and can distinguish the target on both sides of a reference point. The range ambiguity problem caused by image interference in current radar with photonic de-chirping reception is solved. In this study, first, the necessity of I/Q de-chirping is demonstrated. Then, the structure and principle of the proposed photonic-based radar are introduced. A K-band radar with a bandwidth of 8 GHz is established, and an experiment on target detection and inverse synthetic aperture radar imaging is conducted. Results show that the system can effectively suppress the interference from image frequencies. We propose a novel scheme of broadband LFM radar imaging system based on microwave photonic I/Q de-chirping. In the transmitter, a broadband linear frequency modulated signal is generated by photonic frequency-doubling. In the receiver, echoes reflected from the target are simultaneously sent to a couple of modulators in two polarization states. After the bias voltage of the corresponding modulator is adjusted to introduce a 90° phase difference, photonic I/Q de-chirping reception of radar echoes is achieved. The proposed radar is capable of real-time high-resolution detection and can distinguish the target on both sides of a reference point. The range ambiguity problem caused by image interference in current radar with photonic de-chirping reception is solved. In this study, first, the necessity of I/Q de-chirping is demonstrated. Then, the structure and principle of the proposed photonic-based radar are introduced. A K-band radar with a bandwidth of 8 GHz is established, and an experiment on target detection and inverse synthetic aperture radar imaging is conducted. Results show that the system can effectively suppress the interference from image frequencies.
The wings of an airplane vibrate when it is nonstationary. When an airplane is observed using a microwave photonics-based ultrahigh-resolution radar, and this vibration will cause defocusing of the wings. To address this problem, we propose a vibration-parameter estimation method for airplane wings based on microwave-photonics ultrahigh-resolution radar. In this method, we first coarsely separate images of the wings and body of the airplane, and estimate the Light-Of-Sight (LOS) of the radar from a focused and scaled image of the airplane body. Next, we apply sub-aperture imaging to the wings and extract the range and Doppler curves from a sequence of sub-aperture images. By combining the range and Doppler curves with the LOS, we can obtain a preliminary estimation of the vibration parameters. Finally, by Modifying the Polar Format Algorithm (MPFA) and constructing an optimization function that minimizes image entropy, we can obtain accurate vibration parameters. This novel modified polar format algorithm can be applied to complex motion targets, such as an airplane with vibrating wings, swinging ships to effectively decouple range and cross-range dimensional coupling. Experimental results using both simulated and measured data confirm the validity and practicality of the proposed algorithm. The wings of an airplane vibrate when it is nonstationary. When an airplane is observed using a microwave photonics-based ultrahigh-resolution radar, and this vibration will cause defocusing of the wings. To address this problem, we propose a vibration-parameter estimation method for airplane wings based on microwave-photonics ultrahigh-resolution radar. In this method, we first coarsely separate images of the wings and body of the airplane, and estimate the Light-Of-Sight (LOS) of the radar from a focused and scaled image of the airplane body. Next, we apply sub-aperture imaging to the wings and extract the range and Doppler curves from a sequence of sub-aperture images. By combining the range and Doppler curves with the LOS, we can obtain a preliminary estimation of the vibration parameters. Finally, by Modifying the Polar Format Algorithm (MPFA) and constructing an optimization function that minimizes image entropy, we can obtain accurate vibration parameters. This novel modified polar format algorithm can be applied to complex motion targets, such as an airplane with vibrating wings, swinging ships to effectively decouple range and cross-range dimensional coupling. Experimental results using both simulated and measured data confirm the validity and practicality of the proposed algorithm.
We propose a novel injection-locked OptoElectronic Oscillator (OEO) with ultralow phase noise based on two cascaded phase modulators, which is further applied to construct a frequency synthesizer. Thanks to the phase modulation, the output optical spectrum expands and the optical power keeps constant while passing through the optical fiber, which dramatically reduces the intensity noise induced by the nonlinear effects of the optical fiber. A dual-output MZI together with a balanced optical detector realizes the phase modulation to intensity modulation conversion and improves the signal to noise ratio of the OEO. The output frequency of the proposed OEO is 9.9999914 GHz with its sidemode suppression ratio larger than 85 dB, and the phase noise reaches –153.1 dBc/Hz at 10 kHz frequency offset which is 38.7 dB lower than that of Keysight E8257D. Moreover, a broadband, high performance frequency synthesizer is established based on the proposed OEO. Combining the DDS and PLL technologies, the proposed frequency synthesizer can cover 5.9~12.9 GHz range. The phase noise is around –130 dBc/Hz@10 kHz, the spur suppression ratio is better than 65 dB, and the frequency hopping time is less than 1.48 μs. We propose a novel injection-locked OptoElectronic Oscillator (OEO) with ultralow phase noise based on two cascaded phase modulators, which is further applied to construct a frequency synthesizer. Thanks to the phase modulation, the output optical spectrum expands and the optical power keeps constant while passing through the optical fiber, which dramatically reduces the intensity noise induced by the nonlinear effects of the optical fiber. A dual-output MZI together with a balanced optical detector realizes the phase modulation to intensity modulation conversion and improves the signal to noise ratio of the OEO. The output frequency of the proposed OEO is 9.9999914 GHz with its sidemode suppression ratio larger than 85 dB, and the phase noise reaches –153.1 dBc/Hz at 10 kHz frequency offset which is 38.7 dB lower than that of Keysight E8257D. Moreover, a broadband, high performance frequency synthesizer is established based on the proposed OEO. Combining the DDS and PLL technologies, the proposed frequency synthesizer can cover 5.9~12.9 GHz range. The phase noise is around –130 dBc/Hz@10 kHz, the spur suppression ratio is better than 65 dB, and the frequency hopping time is less than 1.48 μs.
In this paper, the development requirements and challenges of phased array radar design are discussed. A new architecture of phased array radar based on microwave photonic technology is proposed, and its technical advantages are explained. Aiming for applications in engineering practice, the main scientific problems and major technical challenges currently faced are concisely presented from the aspects of their core components, basic transmission links, various processing units, and overall systems. The road map of follow-up research work is given and the future development in this field is finally prospected. In this paper, the development requirements and challenges of phased array radar design are discussed. A new architecture of phased array radar based on microwave photonic technology is proposed, and its technical advantages are explained. Aiming for applications in engineering practice, the main scientific problems and major technical challenges currently faced are concisely presented from the aspects of their core components, basic transmission links, various processing units, and overall systems. The road map of follow-up research work is given and the future development in this field is finally prospected.
Microwave photonic integrated chip technology is an important supporting technology of microwave photonic radar. It can not only realize the multifunction of devices, reduce the volume of microwave photonic radar, but also greatly improve the stability and reliability. This paper introduces the photonic integrated chip technologies based on the commonly used InP, Si, LiNbO3 and their heterogeneous integrations and the optoelectronic integration chip technologies for microwave photonics. Finally, the future development trends is discussed. Microwave photonic integrated chip technology is an important supporting technology of microwave photonic radar. It can not only realize the multifunction of devices, reduce the volume of microwave photonic radar, but also greatly improve the stability and reliability. This paper introduces the photonic integrated chip technologies based on the commonly used InP, Si, LiNbO3 and their heterogeneous integrations and the optoelectronic integration chip technologies for microwave photonics. Finally, the future development trends is discussed.