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tiaoping
- 对脉冲多普勒雷达调频噪声进行仿真，你会发现非常又有有用。-FM noise to simulate the radar you will find that it is very useful.thank you to use it.thank you very much.you must be glad to find it.
RFnoise
- 雷达噪声干扰仿真。对雷达的噪声的各种干扰进行matlab仿真-Simulation of radar noise. Variety of radar interference noise matlab simulation
noiseAM
- 雷达噪声干扰仿真。仿真各种雷达的噪声。带有matlab源程序-Simulation of radar noise. Simulation of a variety of radar noise. Source code with matlab
calcCFARthreshold
- 恒虚警率目标检测,计算雷达影像CFAR 阈值，达到雷达影像目标检测的目的-calculates classical radar CFAR threshold for 0-mean AWGN.classical Neyman-Pearson detection threshold for radar detection under additive Gaussian white noise criterion and specifid false alarm probability.
ZSTP
- 赵国庆老师编写的《雷达对抗原理》的噪声调频程序，包含时域、频域及频率谱，并作图。-" Radar against the principle of" noise FM program
ARPAfilter
- 用于航海雷达回波信号的matlab处理程序，虚拟的高斯白噪声-Used marine radar echo signal processing matlab, virtual white Gaussian noise
hundun
- ：针对正交编码信号已有设计方法计算复杂、编码长度和数量受限等问题，该文利用混沌序列类随机、初值 敏感， 易产生和易使用的特点， 提出应用混沌序列设计随机离散频率编码信号。 在给出编码信号设计方案的基础上， 详细推导此类信号的模糊函数，分析了其距离、多普勒分辨能力，讨论了信号的准正交特性，并比较了不同混沌序 列对信号性能的影响。 理论分析和仿真实验表明， 结合混沌序列的频率编码信号具有优良的模糊函数、 准正交性能， 且信号产生容易，编码长度和数量可以任意设置，可以作为一类有潜力的雷
CFAR-detection-algorithm
- A novel constant false alarm rate(CFAR)detection algorithm is proposed in this paper．The Biparameter CFAR detection is applicable tO Gaussian noise in non—coherent integration for radar dim target detection algorithm．The paper analyzed the probab
simulationOfLFMRadar
- 对线性调频脉冲压缩雷达进行了仿真，考虑了实际目标回波包含的系统噪声和地物杂波、高频放大器设计、混频器设计、中频放大器设计、正交鉴相器设计、时域和频域脉冲压缩(脉压)、MTI、MTD及CFAR恒虚警等多个方面。-This code simulates the system of LFM pulse compression radar taking into account of system noise and clutter contained in object signal and many
zz_rarget
- 目标和雷达的仿真程序，可以设置目标位置向量、速度、目标散射截面积、距离门限等等，计入高斯噪声，经过混频和傅里叶变化后再显示其距离和多普勒二维图形。-Target and radar simulation program can be set to the target position vector, velocity, target scattering cross-sectional area, the distance threshold, etc., included in the Ga
AREPS_AD
- 美国AD报告，关于雷达传输损耗预测计算程序AREPS的详细使用报告-AREPS computes and displays radar probability of detection, propagation loss and signal-to-noise ratios, electronic-support-measures (ESM) vulnerability, UHF/VHF communications, and surface-borne surfacesearch
pulsecompresscoherent
- 对雷达多脉冲回波进行匹配滤波处理后，再进行相参积累，提高检测信噪比-Coherent matched filter radar multi-pulse echo, to improve the detection signal to noise ratio
MIMORadarDOAEstimation
- MIMO雷达模型下一种子空间谱估计方法，采用过估计的方法，以避免信源数估计的问题，直接对数据协方差矩阵进行变换，从而构造了信号子空间投影矩阵和噪声子空间投影矩阵，不需要像经典的MUSIC一样对其进行特征分解，完全避开了在一般非理想情况下MUSIC算法必须面对的识别小特征值与大特征值的麻烦，降低了复杂度，而且该方法不受快拍数的影响，在相干源情况下也能准确的估计目标的入射角，不会出现伪峰。-A subspace based DOA (Direction-Of-Arrival) estimation
Gaussn_Clutter
- 高斯噪声杂波处理，用于雷达成像,能够较好地解决对地探测-gaussn noise process,used to radar image
leidahuibofangzhen
- 机载雷达回波的仿真论文，包括信号、杂波及噪声，论述较为具体-Airborne radar echo simulation papers, including the signal, clutter and noise, and discusses more specific
jiagaosibaizaoshengzip
- 本程序产生二次雷达的应答信号，加高斯白噪声，解调成功。-This procedure generated a response of the secondary radar signal plus Gaussian white noise successful demodulation.
Vital-sign-detection-method
- 基于高阶累积量的生命微动信号检测方法的研究成果，发表在IEEE Transaction Geoscience and Remote Sensing 期刊上-The research on vital information extraction meets a lot challenges due to the narrow bandwidth and low signal-to-noise ratio of a vital sign in real environment. In th
Vital-sign-detect
- 基于高阶累积量的生命微动信号检测方法的研究成果，发表在IEEE Transaction Geoscience and Remote Sensing 期刊上-The research on vital information extraction meets a lot challenges due to the narrow bandwidth and low signal-to-noise ratio of a vital sign in real environment. In th
fcnFrostFilter
- fcnFrostFilter performs noise filtering on an image based on an adaptive filter proposed by Frost. [1] V. S. Frost, et al., "A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise," IEEE Trans. Pattern
KalmanFilter
- 卡尔曼滤波的一个典型实例是从一组有限的，包含噪声的，对物体位置的观察序列（可能有偏差）预测出物体的位置的坐标及速度。在很多工程应用(如雷达、计算机视觉)中都可以找到它的身影。同时，卡尔曼滤波也是控制理论以及控制系统工程中的一个重要课题。-A typical example of the Kalman filter, from a limited set, containing the noise, the position of the object observed sequence (the