An effective method of multiple input multiple output （MIMO） radar weak target detection is proposed based on the Hough transform. The detection time duration is divided into multiple coherent processing intervals ...An effective method of multiple input multiple output （MIMO） radar weak target detection is proposed based on the Hough transform. The detection time duration is divided into multiple coherent processing intervals （CPIs）. Within each CPI, conventional methods such as fast Fourier transform （FFT） is exploit to coherent inte- grating in same range cell. Furthermore, noncoherent integration through several range cells can be implemented by Hough transform among all CPIs. Thus, higher integration gain can be obtained. Simulation results are also given to demonstrate that the detection performance of weak moving target can be dramatically improved.展开更多
This paper focuses on the sea-surface weak target detection based on memory-fully convolutional network(M-FCN)in strong sea clutter.Firstly,the constant false alarm rate(CFAR)detection method utilizes a low threshold ...This paper focuses on the sea-surface weak target detection based on memory-fully convolutional network(M-FCN)in strong sea clutter.Firstly,the constant false alarm rate(CFAR)detection method utilizes a low threshold with high probability of false alarm to detect sea-surface weak targets after non-coherent integration.Reducing the detection threshold can generate a large number of false alarms while increasing the detection rate,and how to suppress a large number of false alarms is the key to improve the performance of weak target detection.Then,the detection result of the low threshold is operated to construct the target matrix suitable for the size of fully convolutional networks and the convolution operator form.Finally,the M-FCN architecture is designed to learn the different accumulation characteristics of the target and the sea clutter between different frames.For improving the detection performance,the historical multi-frame information is memorized by the network,and the end-to-end structure is established to detect sea-surface weak target automatically.Experimental results on measured data demonstrate that the M-FCN method outperforms the traditional track before detection(TBD)method and reduces false alarm tracks by 35.1%,which greatly improves the track quality.展开更多
随着雷达技术的广泛应用,雷达也面临诸多挑战,在对微弱目标检测时,由于直达波回波和多径回波同时存在导致无法准确检测到目标,因此通常将多径回波当作干扰。然而,可以利用多径信号中存在的目标信息来优化探测性能。因此,本文提出一种新...随着雷达技术的广泛应用,雷达也面临诸多挑战,在对微弱目标检测时,由于直达波回波和多径回波同时存在导致无法准确检测到目标,因此通常将多径回波当作干扰。然而,可以利用多径信号中存在的目标信息来优化探测性能。因此,本文提出一种新的利用多径信号增强直达波信号的微弱目标增强算法(Multipath Signal Exploitation,MSE),算法通过构造两个位移函数在距离频域慢时间域对回波进行补偿,消除了不同初始距离的影响,将多径信号回波集中在直达波所在位置。然后对补偿后的回波和直达波沿快时间维求和,进一步增强了回波的能量。此外,当存在多个目标时,MSE算法可以消除多径回波的干扰,并且利用多径回波增强多目标的信号能量,以保证在多个目标的多径环境下算法仍然有效。最后进行了仿真实验,结果证明了MSE算法在多目标场景下的有效性。展开更多
在雷达探测领域,由于线性调频(linear frequency modulation,LFM)信号近主瓣区的较高旁瓣电平,强目标旁瓣对弱目标的遮盖现象使得传统雷达对这类弱目标的检测能力大幅下降。对于这一问题,提出一种混沌波形近主瓣区低旁瓣的优化方法。该...在雷达探测领域,由于线性调频(linear frequency modulation,LFM)信号近主瓣区的较高旁瓣电平,强目标旁瓣对弱目标的遮盖现象使得传统雷达对这类弱目标的检测能力大幅下降。对于这一问题,提出一种混沌波形近主瓣区低旁瓣的优化方法。该方法在保持混沌波形优秀的抗截获和抗干扰能力的基础上,结合混沌波形较低的旁瓣电平的特性,充分利用双混沌信号设计的频谱特性和失配滤波器时频自由度来调整脉冲压缩后信号的能量分布。仿真结果表明,所设计的混沌波形具有比较好的距离分辨率,并且经失配滤波器脉冲压缩后的近主瓣区的旁瓣电平达到较低水平,对检测距离相近情况下的弱目标具有一定意义。展开更多
文摘An effective method of multiple input multiple output （MIMO） radar weak target detection is proposed based on the Hough transform. The detection time duration is divided into multiple coherent processing intervals （CPIs）. Within each CPI, conventional methods such as fast Fourier transform （FFT） is exploit to coherent inte- grating in same range cell. Furthermore, noncoherent integration through several range cells can be implemented by Hough transform among all CPIs. Thus, higher integration gain can be obtained. Simulation results are also given to demonstrate that the detection performance of weak moving target can be dramatically improved.
基金This was work supported by the National Natural Science Foundation of China(U19B2031).
文摘This paper focuses on the sea-surface weak target detection based on memory-fully convolutional network(M-FCN)in strong sea clutter.Firstly,the constant false alarm rate(CFAR)detection method utilizes a low threshold with high probability of false alarm to detect sea-surface weak targets after non-coherent integration.Reducing the detection threshold can generate a large number of false alarms while increasing the detection rate,and how to suppress a large number of false alarms is the key to improve the performance of weak target detection.Then,the detection result of the low threshold is operated to construct the target matrix suitable for the size of fully convolutional networks and the convolution operator form.Finally,the M-FCN architecture is designed to learn the different accumulation characteristics of the target and the sea clutter between different frames.For improving the detection performance,the historical multi-frame information is memorized by the network,and the end-to-end structure is established to detect sea-surface weak target automatically.Experimental results on measured data demonstrate that the M-FCN method outperforms the traditional track before detection(TBD)method and reduces false alarm tracks by 35.1%,which greatly improves the track quality.
文摘随着雷达技术的广泛应用,雷达也面临诸多挑战,在对微弱目标检测时,由于直达波回波和多径回波同时存在导致无法准确检测到目标,因此通常将多径回波当作干扰。然而,可以利用多径信号中存在的目标信息来优化探测性能。因此,本文提出一种新的利用多径信号增强直达波信号的微弱目标增强算法(Multipath Signal Exploitation,MSE),算法通过构造两个位移函数在距离频域慢时间域对回波进行补偿,消除了不同初始距离的影响,将多径信号回波集中在直达波所在位置。然后对补偿后的回波和直达波沿快时间维求和,进一步增强了回波的能量。此外,当存在多个目标时,MSE算法可以消除多径回波的干扰,并且利用多径回波增强多目标的信号能量,以保证在多个目标的多径环境下算法仍然有效。最后进行了仿真实验,结果证明了MSE算法在多目标场景下的有效性。
文摘在雷达探测领域,由于线性调频(linear frequency modulation,LFM)信号近主瓣区的较高旁瓣电平,强目标旁瓣对弱目标的遮盖现象使得传统雷达对这类弱目标的检测能力大幅下降。对于这一问题,提出一种混沌波形近主瓣区低旁瓣的优化方法。该方法在保持混沌波形优秀的抗截获和抗干扰能力的基础上,结合混沌波形较低的旁瓣电平的特性,充分利用双混沌信号设计的频谱特性和失配滤波器时频自由度来调整脉冲压缩后信号的能量分布。仿真结果表明,所设计的混沌波形具有比较好的距离分辨率,并且经失配滤波器脉冲压缩后的近主瓣区的旁瓣电平达到较低水平,对检测距离相近情况下的弱目标具有一定意义。
