Modulations and diversities, including the Costas-ordered stepped-frequency and nonlinear stepped-frequency waveforms are widely used in linear frequency modulation （LFM） pulse trains to reduce the relatively high a...Modulations and diversities, including the Costas-ordered stepped-frequency and nonlinear stepped-frequency waveforms are widely used in linear frequency modulation （LFM） pulse trains to reduce the relatively high autocorrelation function （ACF） sidelobes. An efficient method was developed to optimize the interpulse frequency modulation to remove most of the ACF sidelobes about the mainlobe peak, with only a small increase in the mainlobe width. The genetic algorithm is used to solve the nonlinear optimization problem to find the interpulse frequency modulation sequence. The effects on the ACF sidelobes suppression and mainlobe widening are studied. The results show that the new design is superior to the corresponding stepped-frequency LFM signal and weighted stepped-frequency LFM signal in the terms of the ACF sidelobes reduction and mainlobe spread.展开更多
Passive bistatic radar detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure...Passive bistatic radar detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure, which may result in high-level range ambiguity sidelobes. Because the mismatched filter is effective in suppressing sidelobes, it can be used in a passive bistatic radar. However, due to the low signal-to-noise ratio in the reference signal, the sidelobe suppression performance seriously degrades in a passive bistatic radar system. To solve this problem, a novel mismatched filtering algorithm is developed using worst-case performance optimization. In this algorithm, the influence of the low energy level in the reference signal is taken into consideration, and a new cost function is built based on worst-case performance optimization. With this optimization, the mismatched filter weights can be obtained by minimizing the total energy of the ambiguity range sidelobes. Quantitative evaluations and simulation results demonstrate that the proposed algorithm can realize sidelobe suppression when there is a low-energy reference signal. Its effectiveness is proved using real data.展开更多
Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the diffi...Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the difficult processing in mathmatics and expensivecalculation cost.In this paper,neural computing is introduced into the field of the selection ofbinary codes and a new method based’on simulated annealing(SA)is proposed.The experimentsshow that the proposed method is able to select the optimal binary codes with much less timecost than the known methods,furhtermore the optimization selection of the binary codes versusthe calculation cost tradeoff is easier.展开更多
We design a grey wolf optimizer hybridized with an interior point algorithm to correct a faulty antenna array. If a single sensor fails, the radiation power pattern of the entire array is disturbed in terms of sidelob...We design a grey wolf optimizer hybridized with an interior point algorithm to correct a faulty antenna array. If a single sensor fails, the radiation power pattern of the entire array is disturbed in terms of sidelobe level（SLL） and null depth level（NDL）, and nulls are damaged and shifted from their original locations. All these issues can be solved by designing a new fitness function to reduce the error between the preferred and expected radiation power patterns and the null limitations. The hybrid algorithm has been designed to control the array＇s faulty radiation power pattern. Antenna arrays composed of 21 sensors are used in an example simulation scenario. The MATLAB simulation results confirm the good performance of the proposed method, compared with the existing methods in terms of SLL and NDL.展开更多
The underlying topography and forest height play an indispensable role in many fields,including geomorphology,civil engineering construction,forest investigation,and the modeling of natural disasters.As a new microwav...The underlying topography and forest height play an indispensable role in many fields,including geomorphology,civil engineering construction,forest investigation,and the modeling of natural disasters.As a new microwave remote sensing technology with three-dimensional imaging capability,synthetic aperture radar(SAR)tomography(TomoSAR)has already been proven to be an important tool for underlying topography and forest height estimation.Many spectrum estimation methods have now been proposed for TomoSAR.However,most of the commonly used methods are susceptible to noise and inevitably produce sidelobes,resulting in a reduced accuracy for the inversion of forest structural parameters.In this paper,to solve this problem,a nonparametric spectrum estimation method with low sidelobes-the G-Pisarenko method-is introduced.This method performs a logarithmic operation on the covariance matrix to obtain the main scattering characteristics of the objects of interest while suppressing the noise as much as possible.The effectiveness of the proposed method is demonstrated by the use of both simulated data and P-band airborne SAR data from a tropical forest region in Gabon,Africa.The results show that the proposed method can reduce the sidelobes and improve the estimation accuracy for the underlying topography and forest height.展开更多
雷达系统可通过发射稀疏频谱波形(Sparse Frequency Waveform,SFW)克服同频窄带干扰问题,然而SFW通常具有较高的距离旁瓣,降低了弱小目标的检测性能。针对该问题,该文提出一种设计低距离旁瓣SFW的相位编码方法。该方法以联合最小化波形...雷达系统可通过发射稀疏频谱波形(Sparse Frequency Waveform,SFW)克服同频窄带干扰问题,然而SFW通常具有较高的距离旁瓣,降低了弱小目标的检测性能。针对该问题,该文提出一种设计低距离旁瓣SFW的相位编码方法。该方法以联合最小化波形功率谱密度均方差和距离旁瓣为准则建立目标函数,并提出一种基于快速傅里叶变换的循环迭代算法(Cycle Iterative Algorithm,CIA)求解目标函数获得最优相位编码波形。随后将该方法扩展至多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达,设计一组具有良好自/互相关特性SFW的相位编码。该方法沿着使目标函数非递增的方向搜索,且无需求解共轭梯度,计算复杂度低,可快速设计并更新发射波形。仿真结果验证了该方法的有效性与灵活性。展开更多
文摘Modulations and diversities, including the Costas-ordered stepped-frequency and nonlinear stepped-frequency waveforms are widely used in linear frequency modulation （LFM） pulse trains to reduce the relatively high autocorrelation function （ACF） sidelobes. An efficient method was developed to optimize the interpulse frequency modulation to remove most of the ACF sidelobes about the mainlobe peak, with only a small increase in the mainlobe width. The genetic algorithm is used to solve the nonlinear optimization problem to find the interpulse frequency modulation sequence. The effects on the ACF sidelobes suppression and mainlobe widening are studied. The results show that the new design is superior to the corresponding stepped-frequency LFM signal and weighted stepped-frequency LFM signal in the terms of the ACF sidelobes reduction and mainlobe spread.
基金Project supported by the National Natural Science Foundation of China(No.61401526)the 111 Project+1 种基金China(No.B18039)the National Key Laboratory of Science Foundation of Science and Technology on Space Microwave,China(No.614241103030617)。
文摘Passive bistatic radar detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure, which may result in high-level range ambiguity sidelobes. Because the mismatched filter is effective in suppressing sidelobes, it can be used in a passive bistatic radar. However, due to the low signal-to-noise ratio in the reference signal, the sidelobe suppression performance seriously degrades in a passive bistatic radar system. To solve this problem, a novel mismatched filtering algorithm is developed using worst-case performance optimization. In this algorithm, the influence of the low energy level in the reference signal is taken into consideration, and a new cost function is built based on worst-case performance optimization. With this optimization, the mismatched filter weights can be obtained by minimizing the total energy of the ambiguity range sidelobes. Quantitative evaluations and simulation results demonstrate that the proposed algorithm can realize sidelobe suppression when there is a low-energy reference signal. Its effectiveness is proved using real data.
文摘Binary code signals have been widely used in various radars due to their simpleimplementation,but the selection of the binary codes with high comporession ratio and lowsidelobes is not solved well,because of the difficult processing in mathmatics and expensivecalculation cost.In this paper,neural computing is introduced into the field of the selection ofbinary codes and a new method based’on simulated annealing(SA)is proposed.The experimentsshow that the proposed method is able to select the optimal binary codes with much less timecost than the known methods,furhtermore the optimization selection of the binary codes versusthe calculation cost tradeoff is easier.
基金supported by the Ministry of Higher Education(MOHE)the Research Management Centre(RMC)+2 种基金the School of Postgraduate Studies(SPS)the Communication Engineering Department,the Faculty of Electrical Engineering(FKE)Universiti T¨ekùnolóogi Malaysia(UTM)Johor Bahru(Nos.12H09 and 03E20tan)
文摘We design a grey wolf optimizer hybridized with an interior point algorithm to correct a faulty antenna array. If a single sensor fails, the radiation power pattern of the entire array is disturbed in terms of sidelobe level（SLL） and null depth level（NDL）, and nulls are damaged and shifted from their original locations. All these issues can be solved by designing a new fitness function to reduce the error between the preferred and expected radiation power patterns and the null limitations. The hybrid algorithm has been designed to control the array＇s faulty radiation power pattern. Antenna arrays composed of 21 sensors are used in an example simulation scenario. The MATLAB simulation results confirm the good performance of the proposed method, compared with the existing methods in terms of SLL and NDL.
基金supported in part by the National Natural Science Foundation of China[grant number 42101400],[grant number 42171387]in part by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA19070202].
文摘The underlying topography and forest height play an indispensable role in many fields,including geomorphology,civil engineering construction,forest investigation,and the modeling of natural disasters.As a new microwave remote sensing technology with three-dimensional imaging capability,synthetic aperture radar(SAR)tomography(TomoSAR)has already been proven to be an important tool for underlying topography and forest height estimation.Many spectrum estimation methods have now been proposed for TomoSAR.However,most of the commonly used methods are susceptible to noise and inevitably produce sidelobes,resulting in a reduced accuracy for the inversion of forest structural parameters.In this paper,to solve this problem,a nonparametric spectrum estimation method with low sidelobes-the G-Pisarenko method-is introduced.This method performs a logarithmic operation on the covariance matrix to obtain the main scattering characteristics of the objects of interest while suppressing the noise as much as possible.The effectiveness of the proposed method is demonstrated by the use of both simulated data and P-band airborne SAR data from a tropical forest region in Gabon,Africa.The results show that the proposed method can reduce the sidelobes and improve the estimation accuracy for the underlying topography and forest height.
