In this paper,we investigate a distributed multi-input multi-output and orthogonal frequency division multiplexing(MIMO-OFDM) dual-functional radar-communication(DFRC) system,which enables simultaneous communication a...In this paper,we investigate a distributed multi-input multi-output and orthogonal frequency division multiplexing(MIMO-OFDM) dual-functional radar-communication(DFRC) system,which enables simultaneous communication and sensing in different subcarrier sets.To obtain the best tradeoff between communication and sensing performance,we first derive Cramer-Rao Bound(CRB) of targets in detection area,and then maximize the transmission rate by jointly optimizing the power/subcarriers allocation and the selection of radar receivers under the constraints of detection performance and total transmit power.To tackle the non-convex mixed integer programming problem,we decompose the original problem into a semidefinite programming(SDP) problem and a convex quadratic integer problem and solve them iteratively.The numerical results demonstrate the effectiveness of our proposed algorithm,as well as the performance improvement brought by optimizing radar receivers selection.展开更多
Neural network-based methods for intrapulse modulation recognition in radar signals have demonstrated significant improvements in classification accuracy.However,these approaches often rely on complex network structur...Neural network-based methods for intrapulse modulation recognition in radar signals have demonstrated significant improvements in classification accuracy.However,these approaches often rely on complex network structures,resulting in high computational resource requirements that limit their practical deployment in real-world settings.To address this issue,this paper proposes a bottleneck residual network with efficient soft-thresholding(BRN-EST)network,which integrates multiple lightweight design strategies and noise-reduction modules to maintain high recognition accuracy while significantly reducing computational complexity.Experimental results on the classical low-probability-of-intercept(LPI)radar signal dataset demonstrate that BRN-EST achieves comparable accuracy to state-of-the-art methods while reducing computational complexity by approximately 50%.展开更多
The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deterior...The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deteriorates greatly when the FM inter- ference power exceeds the anti-jamming limit of the radar. Accord- ing to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane, while the FM in- terference only concentrates in a small portion, a new method is proposed based on adaptive short-time Fourier transform （STFT） and time-varying filtering for FM interference suppression. This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference. Two types of interference, linear FM （LFM） and sinusoidal FM （SFM）, under different signal-to-jamming ratio （S JR） are studied. It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.展开更多
In the high speed target environment,there exists serious Doppler effect in the low pulse repetition frequency（LPRF） modulated frequency stepped frequency（MFSF） radar signal.The velocity range of the target is lar...In the high speed target environment,there exists serious Doppler effect in the low pulse repetition frequency（LPRF） modulated frequency stepped frequency（MFSF） radar signal.The velocity range of the target is large and the velocity is high ambiguous,so the single method is difficult to satisfy the velocity measurement requirement.For this problem,a novel method is presented,it is a combination of cross-correlation inner frame velocity measurement and range-Doppler coupling velocity measurement.The cross-correlation inner frame method,overcoming the low Doppler tolerance of the cross-correlation between frames,can obtain the coarse velocity of the high speed target,and then the precision velocity can be obtained with the range-Doppler coupling method.The simulation results confirm the method is effective,and also it is well real-time and easy to the project application.展开更多
Radar target probing and measurement are challenging tasks for Radio Frequency Simulation（RFS） with pulse radar signal. Due to the long-time duration of pulse radar signal and the limited space of anechoic chamber, ...Radar target probing and measurement are challenging tasks for Radio Frequency Simulation（RFS） with pulse radar signal. Due to the long-time duration of pulse radar signal and the limited space of anechoic chamber, the reflected signal returns before pulse radar signal is fully transmitted in RFS. As a consequence, the transmitted and reflected signals are coupled at the receiver. To handle this problem, the Interrupted Transmitting and Receiving（ITR） experiment system is constructed in this paper by dividing the pulse radar signal into sub-pulses. The target echo can be obtained by transmitting and receiving the sub-pulses intermittently. Furthermore, the principles of ITR are discussed and the target probing experiments are performed with the ITR system. It is demonstrated that the ITR system can overcome the coupling between the reflected and transmitted signals. Based on the target probing results, the performance of pulse radar target probing and measurement can be verified in RFS with the ITR system.展开更多
This paper presents a joint high order statistics （HOS） and signal-to-noise ratio （SNR） algorithm for the recognition of multiple-input multiple-output （MIMO） radar signal without a priori knowledge of the signa...This paper presents a joint high order statistics （HOS） and signal-to-noise ratio （SNR） algorithm for the recognition of multiple-input multiple-output （MIMO） radar signal without a priori knowledge of the signal parameters. This method is capable of recognizing the MIMO radar signal as well as discriminating it from single-carrier signal adopted by conventional radar. Meanwhile, the sub-carrier number of the none-coding MIMO radar signal is estimated. Extensive simulations are carried out in different operating conditions. Simulation results prove the feasibility and indicate that the recognition probability could reach over 90% when the value of SNR is above 0 dB.展开更多
With appropriate geometry configuration, helicopter- borne rotating synthetic aperture radar （ROSAR） can break through the limitations of monostatic synthetic aperture radar （SAR） on forward-looking imaging. With ...With appropriate geometry configuration, helicopter- borne rotating synthetic aperture radar （ROSAR） can break through the limitations of monostatic synthetic aperture radar （SAR） on forward-looking imaging. With this capability, ROSAR has extensive potential applications, such as self-navigation and self-landing. Moreover, it has many advantages if combined with the frequency modulated continuous wave （FMCW） technology. A novel geometric configuration and an imaging algorithm for helicopter-borne FMCW-ROSAR are proposed. Firstly, by per- forming the equivalent phase center principle, the separated trans- mitting and receiving antenna system is equalized to the case of system configuration with antenna for both transmitting and receiving signals. Based on this, the accurate two-dimensional spectrum is obtained and the Doppler frequency shift effect in- duced by the continuous motion of the platform during the long pulse duration is compensated. Next, the impacts of the velocity approximation error on the imaging algorithm are analyzed in de- tail, and the system parameters selection and resolution analysis are presented. The well-focused SAR image is then obtained by using the improved Omega-K algorithm incorporating the accurate compensation method for the velocity approximation error. FJnally, correctness of the analysis and effectiveness of the proposed al- gorithm are demonstrated through simulation results.展开更多
Modified implementation architecture for sinusoidal frequency modulation is introduced to extract the range information from the received radar echo. Range ambiguity problem arises because the range is calculated from...Modified implementation architecture for sinusoidal frequency modulation is introduced to extract the range information from the received radar echo. Range ambiguity problem arises because the range is calculated from the estimated phase of the received signal which is wrapped into （0, 2π]. By integrating Doppler frequency shifts, the variation of range can be estimated and used as an auxiliary information to help eliminating the corresponding range ambiguity. The performance of the new technique is evaluated by simulations. The results show that this technique is robust to sever phase noise and can be used effectively for ambiguity elimination of the modified sinusoidal frequency modulated continuous wave radar.展开更多
Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributio...Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.展开更多
In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic count...In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval （PRI） of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform （CHT） algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio （SNR） is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.展开更多
Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient im...Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.展开更多
When imaging ocean surface waves by X-band marine radar, the radar backscatter from the sea surface is modulated by the long surface gravity waves. The modulation transfer function （MTF） comprises tilt, hydrodynamic...When imaging ocean surface waves by X-band marine radar, the radar backscatter from the sea surface is modulated by the long surface gravity waves. The modulation transfer function （MTF） comprises tilt, hydrodynamic, and shadowing modulations. A conventional linear MTF was derived using HH-polarized radar observations under conditions of deep water. In this study, we propose a new quadratic polynomial MTF based on W-polarized radar measurements taken from heterogeneous nearshore wave fields. This new MTF is obtained using a radar-observed image spectrum and in situ buoy-measured wave frequency spectrum. We validate the MTF by comparing peak and mean wave periods retrieved from X-band marine radar image sequences with those measured by the buoy. It is shown that the retrieval accuracies of peak and mean wave periods of the new MTF are better than the conventional MTF. The results also show that the bias and root mean square errors of the peak and mean wave periods of the new MTF are 0.05 and 0.88 s, and 0.32 and 0.53 s, respectively, while those of the conventional MTF are 0.61 and 0.98 s, and 1.39 and 1.48 s, respectively. Moreover, it is also shown that the retrieval results are insensitive to the coefficients in the proposed MTF.展开更多
基金supported by the National Key R&D Program of China (2023YFB2905605)the National Natural Science Foundation of China (62072229)。
文摘In this paper,we investigate a distributed multi-input multi-output and orthogonal frequency division multiplexing(MIMO-OFDM) dual-functional radar-communication(DFRC) system,which enables simultaneous communication and sensing in different subcarrier sets.To obtain the best tradeoff between communication and sensing performance,we first derive Cramer-Rao Bound(CRB) of targets in detection area,and then maximize the transmission rate by jointly optimizing the power/subcarriers allocation and the selection of radar receivers under the constraints of detection performance and total transmit power.To tackle the non-convex mixed integer programming problem,we decompose the original problem into a semidefinite programming(SDP) problem and a convex quadratic integer problem and solve them iteratively.The numerical results demonstrate the effectiveness of our proposed algorithm,as well as the performance improvement brought by optimizing radar receivers selection.
基金supported by the National Defense Pre-Research Foundation of China during the“14th Five-Year Plan”under Grant No.629010204.
文摘Neural network-based methods for intrapulse modulation recognition in radar signals have demonstrated significant improvements in classification accuracy.However,these approaches often rely on complex network structures,resulting in high computational resource requirements that limit their practical deployment in real-world settings.To address this issue,this paper proposes a bottleneck residual network with efficient soft-thresholding(BRN-EST)network,which integrates multiple lightweight design strategies and noise-reduction modules to maintain high recognition accuracy while significantly reducing computational complexity.Experimental results on the classical low-probability-of-intercept(LPI)radar signal dataset demonstrate that BRN-EST achieves comparable accuracy to state-of-the-art methods while reducing computational complexity by approximately 50%.
文摘The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deteriorates greatly when the FM inter- ference power exceeds the anti-jamming limit of the radar. Accord- ing to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane, while the FM in- terference only concentrates in a small portion, a new method is proposed based on adaptive short-time Fourier transform （STFT） and time-varying filtering for FM interference suppression. This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference. Two types of interference, linear FM （LFM） and sinusoidal FM （SFM）, under different signal-to-jamming ratio （S JR） are studied. It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.
文摘In the high speed target environment,there exists serious Doppler effect in the low pulse repetition frequency（LPRF） modulated frequency stepped frequency（MFSF） radar signal.The velocity range of the target is large and the velocity is high ambiguous,so the single method is difficult to satisfy the velocity measurement requirement.For this problem,a novel method is presented,it is a combination of cross-correlation inner frame velocity measurement and range-Doppler coupling velocity measurement.The cross-correlation inner frame method,overcoming the low Doppler tolerance of the cross-correlation between frames,can obtain the coarse velocity of the high speed target,and then the precision velocity can be obtained with the range-Doppler coupling method.The simulation results confirm the method is effective,and also it is well real-time and easy to the project application.
基金supported in part by the National Natural Science Foundation of China(Nos.61101180,61401491 and 61490692)
文摘Radar target probing and measurement are challenging tasks for Radio Frequency Simulation（RFS） with pulse radar signal. Due to the long-time duration of pulse radar signal and the limited space of anechoic chamber, the reflected signal returns before pulse radar signal is fully transmitted in RFS. As a consequence, the transmitted and reflected signals are coupled at the receiver. To handle this problem, the Interrupted Transmitting and Receiving（ITR） experiment system is constructed in this paper by dividing the pulse radar signal into sub-pulses. The target echo can be obtained by transmitting and receiving the sub-pulses intermittently. Furthermore, the principles of ITR are discussed and the target probing experiments are performed with the ITR system. It is demonstrated that the ITR system can overcome the coupling between the reflected and transmitted signals. Based on the target probing results, the performance of pulse radar target probing and measurement can be verified in RFS with the ITR system.
基金supported by the Foundation of Chinese People’s Liberation Army General Equipment Department(41101020303)
文摘This paper presents a joint high order statistics （HOS） and signal-to-noise ratio （SNR） algorithm for the recognition of multiple-input multiple-output （MIMO） radar signal without a priori knowledge of the signal parameters. This method is capable of recognizing the MIMO radar signal as well as discriminating it from single-carrier signal adopted by conventional radar. Meanwhile, the sub-carrier number of the none-coding MIMO radar signal is estimated. Extensive simulations are carried out in different operating conditions. Simulation results prove the feasibility and indicate that the recognition probability could reach over 90% when the value of SNR is above 0 dB.
基金supported by the National Basic Research Program of China(2011CB707001)the Fundamental Research Funds for the Central Universities(106112015CDJXY500001CDJZR165505)
文摘With appropriate geometry configuration, helicopter- borne rotating synthetic aperture radar （ROSAR） can break through the limitations of monostatic synthetic aperture radar （SAR） on forward-looking imaging. With this capability, ROSAR has extensive potential applications, such as self-navigation and self-landing. Moreover, it has many advantages if combined with the frequency modulated continuous wave （FMCW） technology. A novel geometric configuration and an imaging algorithm for helicopter-borne FMCW-ROSAR are proposed. Firstly, by per- forming the equivalent phase center principle, the separated trans- mitting and receiving antenna system is equalized to the case of system configuration with antenna for both transmitting and receiving signals. Based on this, the accurate two-dimensional spectrum is obtained and the Doppler frequency shift effect in- duced by the continuous motion of the platform during the long pulse duration is compensated. Next, the impacts of the velocity approximation error on the imaging algorithm are analyzed in de- tail, and the system parameters selection and resolution analysis are presented. The well-focused SAR image is then obtained by using the improved Omega-K algorithm incorporating the accurate compensation method for the velocity approximation error. FJnally, correctness of the analysis and effectiveness of the proposed al- gorithm are demonstrated through simulation results.
基金Sponsored by the Ministerial Level Advanced Research Foundation (323010101-50)
文摘Modified implementation architecture for sinusoidal frequency modulation is introduced to extract the range information from the received radar echo. Range ambiguity problem arises because the range is calculated from the estimated phase of the received signal which is wrapped into （0, 2π]. By integrating Doppler frequency shifts, the variation of range can be estimated and used as an auxiliary information to help eliminating the corresponding range ambiguity. The performance of the new technique is evaluated by simulations. The results show that this technique is robust to sever phase noise and can be used effectively for ambiguity elimination of the modified sinusoidal frequency modulated continuous wave radar.
基金This work was supported by the National Natural Science Foundation of China(91538201)the Taishan Scholar Project of Shandong Province(ts201511020)the project supported by Chinese National Key Laboratory of Science and Technology on Information System Security(6142111190404).
文摘Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.
基金supported by the National Natural Science Foundation of China under Grant 61172116
文摘In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval （PRI） of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform （CHT） algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio （SNR） is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.
文摘Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2013AA09A505)the National Natural Science Foundation of China(Nos.41076119,41176160,41476158)+4 种基金the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Natural Science Youth Foundation of Jiangsu Province(No.BK2012467)the Natural Science State Key Foundation of Jiangsu Province(No.BK2011008)the National Natural Science Youth Foundation of China(No.41206171)the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology(No.S8113078001)
文摘When imaging ocean surface waves by X-band marine radar, the radar backscatter from the sea surface is modulated by the long surface gravity waves. The modulation transfer function （MTF） comprises tilt, hydrodynamic, and shadowing modulations. A conventional linear MTF was derived using HH-polarized radar observations under conditions of deep water. In this study, we propose a new quadratic polynomial MTF based on W-polarized radar measurements taken from heterogeneous nearshore wave fields. This new MTF is obtained using a radar-observed image spectrum and in situ buoy-measured wave frequency spectrum. We validate the MTF by comparing peak and mean wave periods retrieved from X-band marine radar image sequences with those measured by the buoy. It is shown that the retrieval accuracies of peak and mean wave periods of the new MTF are better than the conventional MTF. The results also show that the bias and root mean square errors of the peak and mean wave periods of the new MTF are 0.05 and 0.88 s, and 0.32 and 0.53 s, respectively, while those of the conventional MTF are 0.61 and 0.98 s, and 1.39 and 1.48 s, respectively. Moreover, it is also shown that the retrieval results are insensitive to the coefficients in the proposed MTF.
