一种高动态低信噪比卫星导航信号捕获方法

为提升高动态低信噪比环境下卫星导航信号的捕获性能,提出了一种基于分数阶傅里叶变换(FrFT)及部分匹配滤波(PMF)的捕获方法。在该方法中,接收机首先利用PMF对接收信号做分段相干积分,随后借助快速傅里叶变换(FFT)对分段积分结果做离散快速FrFT,最后通过检测FrFT输出的峰值完成信号的捕获。由于具有多普勒频率变化率的卫星导航信号在FrFT后呈现能量聚焦特性,所提方法能够显著提高信号的长时间相干积分增益。同时对所提算法的捕获概率、平均捕获时间以及算法复杂度等性能指标进行了理论分析及计算机仿真验证。仿真表明,与传统的PMF-FFT方法相比,所提方法能够通过延长相干积分时间的方式有效提升高动态低信噪比卫星导航信号的捕获概率、降低捕获时间。     

Doppler ambiguity resolution using multiple PRF

An algorithm for velocity ambiguity resolution in coherent pulsed Doppler radar using multiple pulse repetition frequencies (PRF) is presented. It relies on the choice of particular values for the PRFs. The folded frequency of the target signal is obtained by averaging the folded frequency estimates for each PRF, and a quasi maximum likelihood criterion is maximized for ambiguity order estimation. The fast implementation of this nonambiguous estimation procedure is based on the fast Fourier transform (FFT), The proposed waveform allows full exploitation of any (even) number of PRFs, which appears to be important for estimation improvement. The effects of the waveform parameters and the folded frequency estimation variance on the performance of the ambiguity order estimation procedure are evaluated theoretically and through computer simulations. Mean square error (MSE) curves are given to assess the Doppler frequency estimation accuracy. Finally, the new method is compared with a classical technique and the implementation of the algorithm in a clutter environment is addressed.     

基于DCT-CS的脉冲星周期超快速估计方法

受快速傅里叶变换（fast Fourier transform，FFT）的影响，基于FFT和压缩感知（compressive sensing, CS）的脉冲星周期快速估计算法的计算量大。为进一步减小计算量并提高计算精度，利用离散余弦变换（discrete cosine transform，DCT)取代FFT，提出了一种基于DCT-CS的脉冲星周期超快速估计算法。在该方法中，利用DCT提取脉冲星信号的低频部分构建低频DCT矩阵；构建畸变轮廓字典并获取累积轮廓；提出了利用最大值超分辨率稀疏恢复估计脉冲星周期的方法。仿真结果表明，DCT-CS的脉冲星周期估计精度达到了3.82×10-12 s，计算时间达到了9.31 ms。与FFT-CS相比，周期估计精度提高了约16%，计算时间缩短了约37.5%，实现了实时高精度的脉冲星周期估计。     

Total information processor for 121.5/243 MHz SARSAT signals

Search and rescue satellite-aided tracking (SARSAT) has certain shortcomings which could possibly be ameliorated by employing a more extensive signal processing strategy. The approach proposed is based on partially compensating for the Doppler shift, which then permits the data processing windows to be increased significantly. Incorporating a ranking technique with the conventional fast Fourier transform (FFT) processor and implementing an autoregressive moving-average estimator provides an optimal strategy that maximizes the probability of detecting the emergency signals     

An efficient SAR parallel processor

A parallel architecture especially designed for a synthetic-aperture-radar (SAR) processing algorithm based on an appropriate two-dimensional fast Fourier transform (FFT) code is presented. The algorithm is briefly summarized, and the FFT code is given for the one-dimensional case, although all results can be immediately generalized to the double FFT. The computer architecture, which consists of a toroidal net with transputers on each node, is described. Parametric expressions for the computational time of the net versus the number of nodes are derived. The architecture allows drastic reduction of the processing time, preserving elaboration accuracy and flexibility     

GPS信号FFT自适应抗干扰技术的FPGA工程实现

针对自适应抗干扰技术展开研究,提出了易于FPGA实现的FFT自适应窄带抗干扰技术.这种方法减小了数字信号处理部分的计算量,提高了系统处理的实时性,降低了系统的复杂程度.实验表明在有宽带干扰存在的情况下,使用所提出的方法可以自适应检测并剔除窄带干扰.与GPS接收机的对接测试表明,该技术能大大提高接收机的抗干扰能力.     

A new algorithm for the formation of ISAR images

A new technique for implementing the enhanced image processing (EIP) algorithm for the formation of inverse synthetic aperture radar (ISAR) images is presented. The EIP algorithm is required when, during the formation of an image, scattering centers on a target move out of range and/or Doppler resolution cells. This phenomenon is common for high resolution imagery of practical-sized targets. The method presented is based entirely on the fast Fourier transform (FFT) and therefore does not require the interpolation schemes that are prevalent in the standard EIP implementation. A brief review of the theory of radar imaging is presented to establish the notation for the work. Following the presentation of the new algorithm, a simple example is given to demonstrate the effectiveness of the new technique. In addition work is presented that demonstrates the processing required to reduce the sidelobes in imagery generated by the EIP technique     

406 MHz ELT signal spectra for SARSAT

The signal format and spectral properties of the 406-MHz emergency locator transmitter (ELT) used in the search and rescue satellite aided tracking (SARSAT) system are examined. The ELT improves location estimate accuracies and can relay information about the particular aircraft and its problem, by means of the digitally modulated message fields. It is shown that due to the RF signal frequency characteristics and the Doppler shift, processing must be performed over a frequency band of approximately 25 kHz. Through the use of the fast Fourier transformation (FFT), the frequency spectrum of the ELT is analyzed, taking account of effects due to noise, multiple simultaneously received signals, and Doppler shift. It is demonstrated that the FFT provides an effective means for detecting and recognizing the presence of one or more ELT signals over this 25-kHz frequency band. Some recommendations are made to improve the spectral characteristics and the performance of the ELT     

基于脉组间频率步进的合成超宽带距离像及速度分析

 对脉组间频率步进信号进行信号处理可直接获得合成超宽带(UWB)距离像及目标速度信息,但由于多普勒色散引入的快速傅里叶变换(FFT)输出失配误差和距离多普勒耦合,导致距离像的失真。介绍消除多普勒色散的影响的方法,分析且补偿距离多普勒耦合对距离像的影响,进一步讨论由测速误差产生的补偿量化误差对距离像的影响,并推导由此导致的距离走动公式。提出的迭代二分逼近法使速度分辨提高 N 倍( N 为脉组个数),从而得到目标真实高分辨距离像。仿真实验结果表明多普勒色散得到消除且 N 的选取更加灵活。     

Efficient wideband signal parameter estimation using a radon-ambiguity transform slice

A novel efficient technique based on a single slice Radon-ambiguity transform (RAT) for time-delay and time-scale estimation is proposed. The proposed approach combines the narrowband cross-ambiguity function (NBCAF), the wideband cross-ambiguity function (WBCAF), and a single slice RAT to estimate multiple target parameters in noisy environments. The square modulus of Gaussian-enveloped linear frequency modulated (GLFM) signals has high-energy centrality in the ambiguity plane. Its peaks in the NBCAF fall along nearly straight lines whose slopes depend on the Doppler rates of the moving targets. These lines could be effectively detected by computing the entire Radon transform of the NBCAF for all possible angles; however, it is a computationally intensive procedure. It is shown that without calculating the entire RAT, it is possible to estimate target parameters using only a single slice of the RAT, i.e., using an appropriate projection of the NBCAF. It is demonstrated that the proposed method can successfully separate overlapping targets efficiently. The efficiency is achieved due to fast Fourier transform (FFT)-bascd processing, use of a single slice of RAT, and the use of only one-dimensional (1-D) searches.     

Real-time mosaicking for infrared videos from an oblique sweeping camera

Image mosaicking is widely used in Geographic Information Systems (GISs) for large-scale ground surface analysis. However, most existing mosaicking methods can only be used in offline processing due to the enormous amounts of computation. In this paper, we propose a novel and practical algorithm for real-time infrared video mosaicking. To achieve this, a novel fast template matching algorithm based on Sum of Cosine Differences (SCD) is proposed to coarsely match the sequential images. The high speed of the proposed template matching algorithm is obtained by computing correlation with Fast Fourier Transform (FFT). We also propose a novel fast Least Squares Matching (LSM) algorithm for inter-frame fine registration, which can significantly reduce the computation without degrading the matching accuracy. In addition, the proposed fast LSM can effectively adapt for noise degradation and geometric distortion. Based on the proposed fast template matching algorithm and fine registration algorithm, we develop a practical real-time mosaicking approach which can produce seamless mosaic image highly efficiently. Experiments on synthetic and real-world datasets demonstrate that the proposed algorithm is not just computationally efficient but also robust against various noise distortions.     

Frequency-Agile Radar Signal Processing

Modern radars may incorporate pulse-to-pulse carrier frequency modulation to increase probability of detection, to reduce Vulnerability to jamming, and to reduce probability of interception. However, if coherent processing is used for clutter rejection, the frequency of N consecutive pulses must be held constant for N-pulse clutter cancellation or Doppler filtering. If M pulses are transmitted during the time the antenna illuminates a target, there are M/N coherently integrated echoes available for noncoherent integration in the computer or the operator's display to further improve the signal-to-noise ratio (SNR). In this paper, analytical and simulation methods are employed to determine the balance between coherent and noncoherent integration that yields the greatest SNR improvement. Attention is focused upon a model using peak selection of fast Fourier transform (FFT) Doppler channels and is compared to a reference model involving only a single Doppler channel. Curves of detectable SNR as a function of M and N are presented for both models.     

Constrained bandwidth waveforms with minimal dilation sensitivity

Bandpass waveforms which have envelopes which are insensitive to this velocity-induced time dilation can be efficiently processed by narrowband receivers in which envelope correlation is fixed and Doppler tested using fast Fourier transform (FFT) processing. The peak level of the waveform ambiguity function (AF) can be used to gauge the distortion of the waveform induced by dilation. The degree of AF attenuation is shown to be proportional to the dilation parameter or velocity, waveform traveling wave (TW) product, and a sensitivity parameter which depends on the envelope function utilized. Classes of symmetric, constrained bandwidth, phase modulated envelope functions which are minimally dilation sensitive (Doppler tolerant) are derived. When the resulting waveforms are used with a simple correlation receiver structure and the echo data is derived from slowly fluctuating point scattering in white Gaussian noise, the receiver becomes an uncoupled joint estimator of delay and dilation (Doppler). In the case of the bandpass waveforms, only odd symmetry of the phase modulation (PM) yields an uncoupled estimator     

An efficient 3-D near-field ISAR algorithm

This paper presents a new three-dimensional (3-D) near-field inverse synthetic aperture radar (ISAR) imaging technique. A 3-D ISAR image can be obtained by processing coherently the backscattered fields as a function of the frequency and two rotation angles about axes which are mutually orthogonal. Most of the existing ISAR algorithms are based on the Fourier transform and as such can tolerate only small amounts of wavefront curvature. Wavefront curvature must be taken into account when imaging an object in the near-field. Near-field ISAR imaging of large objects using a direct Fourier inversion may result in images which are increasingly unfocused at points which are more distant from the center of rotation. An algorithm based on an azimuth convolution between a near-field focusing function and the frequency domain backscattered fields is discussed. This convolution is efficiently implemented by using fast Fourier transform (FFT) techniques. Furthermore, in order to further alleviate the computational load of the algorithm, the discrete Fourier transform (DFT) of the focusing function is evaluated by means of the stationary phase method. Experimental results show that this technique is precise and virtually impulse invariant     

基于自适应陷波滤波器的伺服系统谐振频率估计及抑制

在使用陷波滤波器抑制伺服系统机械谐振时,需要获取准确的机械谐振频率。为了快速检测出谐振频率,提出了一种基于自适应陷波滤波器(ANF)的机械谐振频率估计算法,通过速度误差信号分析,实现谐振频率在线快速辨识。首先,建立柔性连接伺服系统模型;然后,对ANF频率估计算法进行分析,并且与常用的快速傅里叶变换(FFT)频率检测算法的分析精度和计算速度进行对比。数值比较和仿真验证表明,ANF频率估计算法可以更快地实现谐振频率的精确检测。最后搭建试验平台,以ANF频率估计的结果作为陷波器的中心频率,成功实现了电机转速振荡的抑制,验证了该方法的有效性。     

基于旋转滤波矩阵束的异步电机转子断条故障诊断

现有异步电机故障诊断技术存在短时数据分辨率低、硬件开销大等缺点。针对这一问题,提出一种基于短时数据的旋转滤波矩阵束的异步电机转子断条故障诊断新方法。利用矩阵束算法抗噪性能强的优点,准确求出定子电流基频成分,并通过逆、正同步旋转变换,剔除了定子电流中的基频成分。利用矩阵束算法准确估算定子电流故障信号的频率和幅值,突破传统基于快速傅里叶变换(FFT)分析算法分辨率不足的限制。仿真和电机试验共同表明:旋转滤波矩阵束算法可以在短时数据的基础上准确辨识转子断条故障。     

利用脉组间频率步进信号合成UWB距离像及类MUSIC法对速度的高分辨估计(英文)

提出一种称为类多信号分类(CMUSIC)的方法,其利用脉组间频率步进信号,在具有M个脉冲的脉冲串(子带,即窄带)中高分辨估计径向速度。利用此速度估计值补偿距离-多普勒耦合和多普勒色散后,对跨子带进行快速傅里叶变换则可获得合成超宽带高分辨距离像。和其他方法相比,CMUSIC在低信噪比时具有较好的速度估计性能。当M大于具有不同径向速度的目标个数Q时,该方法在小M值下依然有优越的速度估计性能。此外,经过径向速度解模糊后,该方法适应高径向速度运动的目标。随着国防技术的突飞猛进地发展以及高速先进飞行器的涌现,这具有重要的实际价值。仿真结果验证了该方法的可行及有效性。     

Optimum FFT-based frequency acquisition with application toCOSPAS-SARSAT

In the case of a single sinusoid or multiple well-separated sinusoids, a coarse estimator consisting of a windowed Fourier transform followed by a fine estimator which is an interpolator is a good approximation to an optimal frequency acquisition and measurement algorithm. The design tradeoffs are described. It is shown that for the fine-frequency estimator a good method is to fit a Gaussian function to the fast-Fourier-transform (FFT) peak and its two neighbors. This method achieves a frequency standard deviation and a bias in the order of only a few percent of a bin. In the case of short-time stationarity, for a moderate number of averages and for an adaptive threshold detector, only between 0.5 and 1 dB is lost when averaging is traded off for FFT length, in contrast to the asymptotic result of 1.5 dB. The COSPAS-SARSAT satellite system for emergency detection and localization is used to illustrate the concepts. The algorithm is analyzed theoretically, and good agreement is found with test results     

Efficient implementation of Capon and APES for spectral estimation

Both the Capon and APES estimators can be shown to belong to the class of matched-filterbank spectral estimators and can be used to obtain complex spectral estimates that have more narrow spectral peaks and lower sidelobe levels than the fast Fourier transform (FFT) methods. It can also be shown that APES has better statistical performance than Capon. In this paper, we address the issue of how to efficiently implement Capon and APES for spectral estimation     

提高运算速度的素因子分解FFT算法

对一种用素因子分解计算离散傅里叶变换的算法进行了研究。其特点是能用简单的下标映射并以同址方式实现快速离散傅里叶变换运算。运算结果表明该算法可比常规的Ｃｏｏｌｅｙ－Ｔｕｋｅｙ基２算法快３２％。