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雷达检测处理仿真程序，包括噪声背景下的检测，波动目标的检测，检测概率与虚警概率的计算-the simulation code for radar detection,including detection in the presence of noise,detection of fluctuating target, probability of false alarm and probability of detection
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仿真分析积累检测的性能（发现概率、虚警概率与信噪比的关系曲线）。此程序非常完善，很符合老师的要求-Accumulation detection performance ( simulation analysis found that the probability of false alarm probability SNR curve ) . This program is very perfect , and it is consistent with the teacher require
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在检测与估计中 仿真给出检查概率与虚警概率的关系 Pfa=1-Q(z),Pd=1-Q(z-d),画不同d情况下Pfa与Pd的关系图-In the detection and estimation of simulation shows that the relationship between the check probability and false alarm probability Pfa = 1-Q (z), Pd = 1-Q (zd), PFA and Pd diagram Vid
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频谱感知中的能量感知算法，在不同虚警概率的情况下，信噪比和检测概率的变化。-In Cognitive Radio， spectru sensing is important。And energy detection is more. In different false alarm probability, the Pd vary with the SNR.
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基于能量检测法的matlab程序，很简单，讨论了在不同虚警概率下检测概率的变化和信噪比的要求，自己编的-Based on energy detection method matlab program, very simple, discusses the different detection probability of false alarm probability changes and SNR requirements, own ...
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认知无线电中的加权协作频谱检测算法，用matlab仿真，获得算法的检测概率和虚警概率。-Weighted cooperative cognitive radio spectrum detection algorithm, using matlab simulation, obtain the probability of detection and false alarm probability algorithm.
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使用matlab仿真chirp信号模型应用于GPS捕获中的虚警概率-Chirp signal using matlab simulation model was used to capture the false alarm probability of GPS
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The receiver performance is quantified by depicting the receiver operating char- acteristics (ROC) curves. This curves serve as a tool to and study the performance of a sensing scheme. ROC graphs are employed to show trade-of vs between detection pro
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应用在认知无线电频谱检测中。环境：经过加性白噪声的信号。功能：求解虚警概率和漏检概率。-Used in cognitive radio spectrum detection.Environment: after additive white noise signal.Function: to solve the false alarm probability and missed detection probability.
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在一定的虚警概率下，检测概率随着信噪比的增大而增大-Under a certain false alarm probability, the detection probability increases with the increase of the signal to noise ratio.
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认知无线电合作感知，合作下的检测和虚警概率关系以及最有门限选择-Cognitive radio cooperative sensing, detection and false alarm probability relations and cooperation under the most threshold selection
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认知无线中的能量检测，仿真了高斯信道和瑞利信道的检测概率、虚警概率与判决门限的关系曲线以及两者之间的关系曲线-The detection probability, false alarm probability and the decision threshold of the Gauss channel and the Rayleigh channel are simulated by the energy detection in cognitive radio.
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介绍了检验概率、虚警概率和信噪比之间的关系，并对其进行了仿真验证。-Inspection probability and false alarm probability are introduced and the relationship between the SNR, and the simulation verification.
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恒虚警检测仿真程序，模拟雷达信号检测。得出虚警概率后，计算发现概率,定义信噪比为幅度比。-CFAR simulation program to simulate the radar signal detection. After obtaining the false alarm probability, calculated that the probability amplitude ratio is defined as the signal to noise ratio.
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CFAR即恒虚警检测，是雷达信号处理领域的经典处理算法，其核心是在保证虚警概率一定的条件下，尽可能提高检测概率-CFAR that is constant false alarm detection, radar signal processing field of the classic algorithm, its core is to ensure that the false alarm probability of certain conditions, as far as possi
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瑞利杂波背景下，虚警概率和目标概率在均匀环境，多目标环境，和杂波墙环境下的仿真-Rayleigh clutter, false alarm probability and probability simulation target in a homogeneous environment, multi-target environment, under the walls and clutter the environment
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蒙特卡罗ROC曲线的绘制，包括检测概率，虚警概率等(Monte Carlo ROC curve drawing, including detection probability, false alarm probability and so on)
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多重相关系数的ROC曲线，说明此算法的检测概率与虚警概率的性能比其他经典频谱感知算法更好(The ROC curves of multiple correlation coefficients show that the performance of detection probability and false alarm probability of this algorithm is better than that of other classical spectrum sensing
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在雷达信号检测中，当外界干扰强度变化时，雷达能自动调整其灵敏度，使雷达的虚警概率保持不变。具有这种特性的接收机称为恒虚警接收机。(In radar signal detection, the radar can automatically adjust its sensitivity when the external interference intensity changes, so that the radar's false alarm probability remains uncha
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基于高斯分布的CFAR检测算法(双参数CFAR检测)，输入一个确定的虚警概率，在满足一定虚警率的情况下对图像进行分割，实现目标与背景的分离。(The CFAR detection algorithm based on Gauss distribution (two-parameter CFAR detection) inputs a certain false alarm probability, and segmentes the image to achieve the separation
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