Output Signal-to-Noise Ratios for Amplitude-Modulated Noise-Like Lasers

A general expression of the output SNR of a photodetector is derived for a noise-like laser amplitude-modulated by a stationary Gaussian random modulating signal in the presence of a background light. The electric field Vx(t) of the noise-like laser is assumed to be a stationary narrowband Gaussian random process with zero mean. Two types of modulating signal are considered, the baseband and bandpass modulating signals. More specifically, the effects of the center frequency of the modulating signal, the modulating degree, the bandwidth ration of the noise-like laser to the modulating signal, the effective average quantum rate, and input CNR on output SNR are studied. The detection characteristics of the noise-like laser are also made clear by comparison with the case of a coherent laser.     

Maximun Posterion Probability Demodulation of Angle-Modulated Signals

An algorithm is presented for maximum posterior probability (MPP) demodulation of angle-modulated signals. A sampled data version of the problem is considered, in which additive Gaussian noise and Gaussian modulating signal are assumed. The algorithm is a numerical method for solving the nonlinear equations which are necessary conditions for MPP estimation. Results of a simulation of the algorithm are presented and discussed. Improvements in performance with respect to a phaselocked loop appear to stem from use of data before and after the time position of a phase estimate and from optimization of performance at low signal-to-noise ratio (SNR) as well as at high SNR.     

宽带信号角跟踪和四通道单脉冲方案

分析了宽带信号角跟踪的特殊问题及其实现方案。基于互相关函数的角误差检测方法,推导出了在非相关噪声及相关噪声背景下差路信号的输出信噪比及其角度随机误差的数学表达式,进而给出了带宽增益和最佳带宽的概念,以及提高输出信噪比的方法。为了在低载噪比（C/N）时获得角捕获所需要的和路信号以及差路的归一化信号,提出了四通道单脉冲方案。最后归纳出了低C/N时宽带信号角捕获和角跟踪的几种方法并提出了建议。     

基于独立成分分析的混合LFM信号检测

混合LFM信号广泛存在于实际信号环境巾,对其检测极其重要。对有严重交叉项的混合LFM信号的检测十分困难,因此提出了一种基于独立成分分析的混合LFM信号检测法。通过盲源分离提取各独立成分,利用时频分布矩阵的联合对角化法抑制交叉项,再由各成分信号自项求和重构Wigner-Ville分布,采用Wigner-Hough检测各LFM成分。分析了Wigner-Hough变换输入信噪比和输出信噪比的关系,仿真验证了算法的有效性,得出随着样本点数的增加,在低信噪比条件下,能获得好的检测性能的结论：     

Signal Resolution via Digital Inverse Filtering

Research in numerous areas is directed toward the resolution of multiple overlapping signals in a noisy environment. These areas include radar, sonar, speech, seismology, and electrophysiology. Sometimes matched filters are used; other times inverse filters are employed. This paper discusses one approach to the analysis of the resolution of inverse filters. Our method is to compromise the trade-off between signal resolution and the output signal-to-noise ratio (SNR). A performance measure for the inverse or deconvolution filter is defined as a quantity proportional to the harmonic mean of the resolution and the SNR. An optimum output pulse duration is obtained using this criterion, where the pulse shape has been previously selected and the input signal waveform is known. In addition, upper and lower bounds for the output pulse duration are presented. Graphs are given which allow the designer to select the optimum inverse filter output pulse duration for a desired signal resolution and an estimated SNR.     

Coarse quantization for data compression in coherent location systems

When emitter location systems measure time-difference-of-arrival (TDOA) and differential Doppler (DD) by coherently cross-correlating the signal pairs, data compression techniques are needed to facilitate data transfer of one of the signals to the receiving site of the other signal. Two block-adaptive quantization schemes are analyzed here to determine their impact on the signal-to-noise ratio (SNR) of the quantized signal as well as on the post-correlation SNR. Comparisons are made between two approaches: quantization of the real/imaginary (R/I) components or the magnitude/phase (M/P) components. For the M/P approach, a rule is derived for optimally allocating the bits between the magnitude and phase. The M/P approach provides better post-quantization/precorrelation SNR for most signals; however, when the SNR of the signal not being quantized is small, the post-correlation SNR can be largely unaffected by the quantization. In that case, there is little difference between R/I and M/P, even under the most favorable scenario for M/P.     

软件化雷达发射系统设计

讨论了实现软件化雷达发射系统的一种方法;给出了软件化雷达发射系统的数学模型;给出了产生基带波形的几种设计方案以及几种雷达信号调制算法及软件实现设计图。     

On the Optimum Design of PCM Signals with System Constraints

This paper considers the design of PCM signals with system constraints using Pontryagin's maximum principle. The transmitter signal as well as the correlation signal are determined while maximizing the output signal-to-noise ratio. Both the single and three-pole transmitter filters are considered. An upper bound has been obtained on the performance of PCM signals with constraints.     

Exploiting GNSS signal structure to enhance observability

There are a number of different error sources, such as multipath and thermal noise, which corrupt satellite navigation waveforms from their theoretical structure. However, even under ideal conditions the broadcast signals have some degree of deformation as a result of the practical individual hardware implementation. For the most demanding users of satellite navigation, such as aircraft navigation and landing systems, it is important to characterize the nominal signal structure in order to detect minimal variations resulting from hardware-based errors. Thus far such precorrelation Global Navigation Satellite System (GNSS) signal quality monitoring has been performed through high gain antennas, which allow for raising the GNSS spectrum above the thermal noise floor and observing the structure of the signal directly at the front end output. This paper describes a new approach to achieve such observability based on signal processing techniques, such as dithering and averaging, which leverage the repetitive nature of the GNSS signal. The paper presents how these techniques can drastically improve the signal-to-noise ratio (SNR) in postprocessing, allowing for the direct analysis of GNSS signals using traditional front end designs and conventional antennas. Results are predicted using the appropriate theory and validated using data collected from the Global Positioning System (GPS).     

Error Analysis of the Optimal Antenna Array Processors

The optimal weights of an antenna array processor, which maximizes the output signal-to-noise ratio (SNR) in the absence of errors, are computed using the noise-alone matrix inverse (NAMI) and the steering vector in the look direction or the signal-plus-noise matrix inverse (SPNMI) and the steering vector. In practice the estimated steering vector as well as the estimated optimal weights are corrupted by random errors. This paper has analyzed the effects of these errors on the performance of the NAMI processor and the SPNMI processor by deriving analytic expressions for the output signal power, output noise power, output SNR, and the array gain as a function of the error variance. The treatment is for a general array configuration and no assumption about a particular array geometry is made.     

Effect of Sampling Time Jitter on Array Performance

The effect on array SNR of errors in sampling times (jitter) isan analyzed for the "Bryn processor." Jitter is modeled as a discrete-paramter er random process, and expressions for array SNR are determined as a function of signal and noise spectra and jitter characteristics. For a plane wave signal, it is found that jitter in the data used to design the processor has no effect on output SNR if the noise is independent between channels. However, jitter in the input (evaluation) n) data can cause a substantial loss in peak array SNR and in the array's frequency selectivity. These losses can be expected to increase as the high-frequency content of the data increases. The Bryn processor also loses its interpretation as a likelihood ratio processor in the presence of jitter. The effect of jitter can be reduced in many cases by increasing the sampling rate.     

Detection of Known Signals in Nonstationary Noise

The basic design of a nonlinear, time-invariant filter is postulated for detecting signal pulses of known shape imbedded in nonstationary noise. The noise is a sample function of a Gaussian random process whose statistics are approximately constant during the length of a signal pulse. The parameters of the filter are optimized to maximize the output signal-to-noise ratio (SNR). The resulting nonlinear filter has the interesting property of approximating the performance of an adaptive filter in that it weights each frequency band of each input pulse by a factor that depends on the instantaneous noise power spectrum present at that time. The SNR at the output of the nonlinear filter is compared to that at the output of a matched filter. The relative performance of the nonlinear system is good when the signal pulses have large time-bandwidth products and the instantaneous noise power spectrum is colored in the signal pass band.     

Reference Loop Phase Shift in Adaptive Arrays

Adaptive arrays for use in communication systems require the generation of a so-called reference signal, which is usually derived from the array output. A particular problem associated with this technique, the problem of reference loop phase shift, is discussed. It is shown that phase shift in the reference loop causes the array weights to cycle, and also causes the array to frequency-modulate the signal. In spite of this frequency change, the array maintains a maximum SNR at the output.     

Probablity of Detection for ICW Radars

Eclipsing of received signals is analyzed for Interrupted Continuous Wave (ICW) radars. A probability density for the Signal to Noise Ratio (SNR) at the Doppler filter output is derived which incorporates eclipsing effects and a fluctuating target cross section model. The probability of detection as a function of SNR is calculated for typical ICW parameters and the magnitude of the detection loss due to eclipsing is assessed     

Interference Canceler Array with Reference Generating Loop

Adaptive arrays utilizing an internally generated reference signal to drive least mean square (LMS) weight determining loops have experienced difficulty arising from phase shifts induced by the reference generating circuits. The phenomenon observed is that the expected value of the weights oscillate in the steady state modulating the incoming signal. A scheme is reported which avoids this problem. It differs from earlier methods in that the reference generator has no infinite limiter so that the amplitude of the reference is not constant and in that one element is left unweighted. Alternative schemes were considered wherein the reference signal is drawn from all the array elements or from the weighted elements only. Only the latter is fully reported here, and is found superior. It is shown that in the presence of a desired signal and independent element noise, the processing scheme proposed produces weights whose expected values converge to a constant nonoscillatory state provided certain mild constraints are satisfied. In particular, if a cos ? ? 1, a being the gain and ? the phase shift of the filter in the reference generator, the weights converge. In addition, the steady state signal-to-noise power ratio (SNR) is determined. It is found that with a cos ? close to unity the SNR is that of an (N-1) element array coherently combined, where N is the number of elements. The SNR falls off with departures of a and ? from 1 and 0, respectively, but not drastically.     

A direct position determination method with combined TDOA and FDOA based on particle filter

The localization of a stationary transmitter using moving receivers is considered. The original Direct Position Determination (DPD) methods, with combined Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA), do not perform well under low Signal-to-Noise Ratio (SNR), and worse still, the computation cost is difficult to accept when the computational capabilities are limited. To get better positioning performance, we present a new DPD algorithm that proves to be more computationally efficient and more precise for weak signals than the conventional approach. The algorithm partitions the signal received with the same receiver into multiple non-overlapping short-time signal segments, and then uses the TDOA, the FDOA and the coherency among the short-time signals to locate the target. The fast maximum likelihood estimation, one iterative method based on particle filter, is designed to solve the problem of high computation load. A secondary but important result is a derivation of closed-form expressions of the Cramer-Rao Lower Bound (CRLB). The simulation results show that the algorithm proposed in this paper outperforms the traditional DPD algorithms with more accurate results and higher computational efficiency, and especially at low SNR, it is more close to the CRLB.     

基于周期FRFT的多分量LFMCW雷达信号分离

 多分量线性调频连续波(LFMCW)信号的截获和特征提取是雷达情报侦察的难点,为了实现对多分量LFMCW信号的快速检测和有效分离,提出了一种基于周期分数阶Fourier变换(PFRFT)的多分量LFMCW雷达信号分离新方法。首先介绍了PFRFT,分析了PFRFT和FRFT之间的关系,讨论了LFMCW信号的PFRFT特征。然后给出了一种离散PFRFT的计算方法,结合周期分数阶Fourier域(PFRFD)的窄带滤波和CLEAN算法实现了多分量LFMCW信号的分离。仿真结果表明:①PFRFT的计算效率较周期Wigner-Hough变换(PWHT)具有明显优势;②LFMCW信号分量在特定PFRFD中具有能量峰值,分离后能较好保留时频特征;③当两个LFMCW信号分量的功率相差较大时,适合在PFRFD分离,反之适合在时域分离;④当信噪比(SNR)为0 dB时,两个具有相同功率的LFMCW信号分量分离后,与初始信号分量的相关系数都达到了0.9以上。     

Radiometric detection of spread-spectrum signals in noise ofuncertain power

The standard analysis of the radiometric detectability of a spread-spectrum signal assumes a background of stationary, white Gaussian noise whose power spectral density can be measured very accurately. This assumption yields a fairly high probability of interception, even for signals of short duration. By explicitly considering the effect of uncertain knowledge of the noise power density, it is demonstrated that detection of these signals by a wideband radiometer can be considerably more difficult in practice than is indicated by the standard result. Worst-case performance bounds are provided as a function of input signal-to-noise ratio (SNR), time-bandwidth (TW) product and peak-to-peak noise uncertainty. The results are illustrated graphically for a number of situations of interest. It is also shown that asymptotically, as the TW product becomes large, the SNR required for detection becomes a function of noise uncertainty only and is independent of the detection parameters and the observation interval     

GPS多径信号的自适应滤波估计方法

 研究全球定位系统(GPS)多径信号估计的问题。通过分析自适应滤波器的原理,建立了数字中频信号处理的数学模型,提出一种用自适应滤波实现GPS多径幅度、码相位和载波相位估计的方法。该方法采用不同延迟的伪随机序列对信号进行解扩、解调和累加,得到了作为期望信号的系列自适应滤波相关值。对该方法与其他3种方法进行了理论上的分析比较,得出本方法具有信噪比高、自适应滤波性能好、带有码相位信息和不存在载波模糊度问题等优点。根据各种滤波器算法的特点和本应用的需求,给出了选用递归最小二乘算法实现的方法。通过计算机仿真,验证了提出的方法能够在14 dB的信噪比下,以1个采样间隔的时间延迟分辨率和0.005周的载波相位估计精度估计出GPS L1的多径信号。     

基于四阶累积量和小波降噪的干扰抑制算法

针对盲信号分离算法在低信噪比下分离效果较差的情况,提出了一种基于四阶累积量和小波降噪的含噪盲分离算法,并将该算法用于卫星通信干扰抑制。首先,利用基于四阶累积量的盲分离算法进行信扰盲分离;然后对分离出的已被噪声污染的通信信号进行小波降噪处理。最后,对提出的算法在单音干扰下进行了性能仿真。仿真结果表明,该算法不仅使抗噪性能提高了3dB左右,而且在低信噪比下对强单音干扰具有较好的抑制效果。