Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar(ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the fram...Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar(ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the frame operator properties. In this paper, the relationship between the best achievable ISAR image and the reconstructed image from radar returns was derived in the framework of Finite Frame Processing theory. We show that image defocusing caused by the use of an incorrect target rotation rate is interpreted under the FP method as a frame operator mismatch problem which causes energy dispersion. The unknown target rotation rate may be computed by optimizing the frame operator via a prominent point. Consequently, a prominent intensity maximization method in FP framework was proposed to estimate the underlying target rotation rate from radar returns. In addition, an image filtering technique was implemented to assist searching for a prominent point in practice. The proposed method is justified via a simulation analysis on the performance of FP imaging versus target rotation rate error.Effectiveness of the proposed method is also confirmed from real ISAR data experiments.展开更多
针对全卷积神经网络对单帧红外图像行人检测计算量大、检测率较低等问题,提出了一种改进的LeNet-7系统对红外图像行人检测的方法。该系统包含3个卷积层、3个池化层,通过错误率最小的试选法确定每层参数,以波士顿大学建立的BU-TIV数据库...针对全卷积神经网络对单帧红外图像行人检测计算量大、检测率较低等问题,提出了一种改进的LeNet-7系统对红外图像行人检测的方法。该系统包含3个卷积层、3个池化层,通过错误率最小的试选法确定每层参数,以波士顿大学建立的BU-TIV数据库训练系统。首先,以俄亥俄州立大学建立的OTCBVS和Terravic Motion IR Database红外数据库作为测试图像;然后,采用自适应阈值的垂直和水平投影法得到感兴趣区域(regions of interest,ROI);最后,将得到的ROI输入训练好的系统进行测试。3个测试集检测实验表明,本文方法具有良好的识别能力,与不同实验方法相比,本文方法能有效提高检测率。展开更多
基金Partially supported by Australian Air Force Office of Scientific Research(AFOSR)Grant(FA2386-13-1-4080)
文摘Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar(ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the frame operator properties. In this paper, the relationship between the best achievable ISAR image and the reconstructed image from radar returns was derived in the framework of Finite Frame Processing theory. We show that image defocusing caused by the use of an incorrect target rotation rate is interpreted under the FP method as a frame operator mismatch problem which causes energy dispersion. The unknown target rotation rate may be computed by optimizing the frame operator via a prominent point. Consequently, a prominent intensity maximization method in FP framework was proposed to estimate the underlying target rotation rate from radar returns. In addition, an image filtering technique was implemented to assist searching for a prominent point in practice. The proposed method is justified via a simulation analysis on the performance of FP imaging versus target rotation rate error.Effectiveness of the proposed method is also confirmed from real ISAR data experiments.
文摘针对全卷积神经网络对单帧红外图像行人检测计算量大、检测率较低等问题,提出了一种改进的LeNet-7系统对红外图像行人检测的方法。该系统包含3个卷积层、3个池化层,通过错误率最小的试选法确定每层参数,以波士顿大学建立的BU-TIV数据库训练系统。首先,以俄亥俄州立大学建立的OTCBVS和Terravic Motion IR Database红外数据库作为测试图像;然后,采用自适应阈值的垂直和水平投影法得到感兴趣区域(regions of interest,ROI);最后,将得到的ROI输入训练好的系统进行测试。3个测试集检测实验表明,本文方法具有良好的识别能力,与不同实验方法相比,本文方法能有效提高检测率。