ID 原文 译文
20045 针对此问题，该文提出一种时空域联合的未知线谱目标检测方法(STJD)。 For this issue, a Space-Time Joint Detecion(STJD) method of detecting the unknown line-spectrum target by space-time domain processing is proposed.
20046 首先，利用线谱信号的相干特性，构建了一种能够自主匹配未知线谱信号的时空域联合滤波器，用以滤除接收信号中的宽带背景干扰及噪声。 Firstly, a space-time filter that autonomously matches the unknown line-spectrum signals is constructed tofilter out the broadband interferences and noise.
20047 之后，对滤波信号进行常规频域波束形成得到空时2维波束输出，其具有相对纯净的线谱谱峰。 Secondly, the conventional frequency domain beamforming isperformed on the filtered signals, and then a space-time two-dimensional beam output with relatively pure line-spectrum spectral peaks is obtained.
20048 在此基础上提取线谱并利用线谱信息计算空间方位谱，进而实现对线谱目标的检测。 The line-spectrum signals are extracted from the space-time two-dimensional beam output, and the spatial spectrum is calculated using the extracted line-spectrum information.Then, the detection of the line-spectrum target is realized.
20049 理论推导及仿真结果表明该文方法能够对未知线谱信号进行最小均方误差意义下的时空滤波，并能充分地利用线谱信息进行线谱目标的被动检测。 Theoretical derivation and simulation results verify that the proposed method performs the spatio temporal filtering on the unknown line-spectrum signals in the minimum mean square error sense, and fully utilizes the line-spectrum information for the passive detection of underwater line-spectrum target.
20050 与已有基于线谱特征的线谱目标检测方法相比，该文方法对信噪比(SNR)的要求较低，在多目标、多线谱等复杂情况下具有较好的线谱目标检测性能。 Compared with the existing line-spectrum target detection methods utilizing the line-spectrum features, the proposed method requires lower Signal to Noise Ratio (SNR), and has better detection performance under the complex multi-target multi-spectrum-line conditions.
20051 在复杂的室内环境中，测得的接收信号强度(RSS)值会出现不同程度的波动，导致无法准确地刻画出无线信号传播模型。 In complex indoor environment, the measured Received Signal Strength (RSS) values will fluctuate indifferent degrees, which lead to inaccurate characterization of wireless signal propagation model.
20052 为了解决这个问题，在基于Wi-Fi测距定位模型下，该文提出一种普适的粗粒度定位方法。 To solve thisproblem, a universal coarse grained localization method is proposed based on the Wi-Fi ranging location model.
20053 该方法通过对测量到的RSS值进行拟合，以此获取信号的传播模型； This method gets the signal propagation model by fitting the measured RSS value.
20054 在此基础上计算出未知节点与接入点(AP)的距离，再利用天牛须算法实现未知节点定位，通过仿真验证此传播模型的性能以及该优化算法的有效性。 On this basis, the distancebetween the unknown node and the Access Point (AP) is calculated, then the location of the unknown node isrealized by the beetle antennae search algorithm. The performance of the propagation model and the effectiveness of the optimization algorithm are verified by simulation.