基于两级压缩感知的脉冲星时延估计方法

为了快速获得高精度的脉冲星累积脉冲轮廓时延估计,提出了一种基于两级压缩感知的时延估计方法.压缩感知主要包括三个部分:字典、测量矩阵、恢复算法,其中字典尺寸是影响压缩感知估计精度的重要因素.针对压缩感知中字典的原子数增加虽能提高估计精度但又带来计算量大的问题,该方法采用粗估计与精估计两级字典相结合,先利用粗估计字典原子间隔大的特点进行累积脉冲轮廓全相位估计,得到预估时延值,再利用精估计字典的原子间隔小且个数少适合局部估计的特点对累积脉冲轮廓进行精确时延估计.理论分析与实验结果表明:两级字典数据量比传统字典小两个数量级,在相同的时延估计精度下,该方法比传统压缩感知方法计算量大幅度减少,是一种能保持高估计精度并有效降低计算量的脉冲星时延估计方法.     

浅海多径时延估计的功率谱加权自相关方法

针对浅海近距离时倒谱多径时延峰变弱难以提取的问题,提出了一种功率谱加权自相关多径时延估计方法。该方法采用FFT估计信号功率谱,对功率谱取1-α次幂(0<α<1),再进行IFFT变换,对其实部进行峰值检测获得多径时延估计。根据目标能量通过特性在正横前递增正横后递减的特点,在已检测时延前后一定区间内搜索下一个时延值,实现多径时延的自动提取.理论分析表明,多径时延估计的倒谱法与自相关法都可以看作功率谱加权自相关法的特例.海试数据处理与基于Bellhop射线模型的仿真计算表明,该方法在近距离时多径时延峰比倒谱法更清晰,输出信噪比提高了3~4 dB.采用该方法自动提取的海底反射多径时延用于单个水听器对目标距离的估计,与GPS测量距离基本相符,验证了方法的有效性.      

基于两次谱分析的时延估计方法研究

时延估计是目标定位跟踪系统的关键技术之一,在水声、雷达、声探测等领域广泛应用。时延估计的基本方法是互相关法和相位谱法。互相关法时延估计分辨率与信号带宽近似成反比,因此很难估计多目标时延。相位谱时延估计只能估计单目标时延,并且存在相位解绕问题。本文提出了两次谱分析时延估计方法,即将互功率谱函数再次进行谱估计,二次谱峰值位置间距即为时延估计,这种方法既能够估计单目标时延,又能够估计多目标时延,并且不用相位解绕。仿真计算验证了两次谱时延估计方法的可行性。     

基于时延估计的分裂阵时域波束形成技术

大孔径拖曳线列阵受舰艇横向机动、洋流影响和水动力影响时会产生一定的阵形畸变,阵形畸变使得波束形成时阵列流型失配,进而降低了目标方位分辨率和阵处理的增益。在无法进行阵形估计时,基于时延估计的分裂阵时域波束形成技术将大孔径拖曳线阵分为左右两个子阵分别做波束形成,通过加权广义相关时延估计算法估算对应波束的时延差,再依据估算时延差对左右两个波束进行延时求和得到最终的波束信号。仿真和海试数据证明,相对于全阵直接做波束形成的方法,基于时延估计的分裂阵的时域波束形成技术有效提高了目标方位分辨率和阵处理的增益。     

Comparison of SAFT and two-dimensional deconvolution methods for the improvement of resolution in ultrasonic B-scan images

This Paper compares the properties of the well known synthetic aperture focusing technique (SAFT) with those of two deconvolution methods, which have previously been less widely applied to digitized ultrasonic data. The linear deconvolution method of Wiener filtering and the non-linear maximum entropy method are applied to two-dimensional unrectified (RF) B-scan data, to improve the resolution simultaneously in the lateral and range directions. With SAFT, only an improvement in lateral resolution is possible. Data from linear scans of several unfocussed transducers over machined reflectors at different depths in steel were collected and used to quantify the resolution obtainable by the three processing methods. Wiener filtering is shown to give higher lateral resolution than SAFT processing, by factors of between 1.3 and 2, depending on the depth of the reflector. Maximum entropy gives even higher apparent lateral resolution, but has a tendency to underestimate reflector size. The improvement in range resolution obtainable with Wiener filtering was approximately a factor of 1.5, whereas maximum entropy gave corresponding factors of between 1.7 and 5. For far-field reflectors, deconvolution of rectified (envelope-detected) data is shown to give inherently lower lateral resolution than the deconvolution of the equivalent RF data.     

一种通用的卫星导航信号码时延估计误差评估方法

卫星导航信号的码时延估计误差是决定系统服务性能的关键因素,迫切需要对多种不同调制与复用方式的导航信号进行全面的码时延估计误差性能评估,从而为后期的系统应用提供重要的选择依据.为此,本文提出了通用的码时延估计误差评估方法.首先,概括了导航接收机的码跟踪环路模型,根据是否匹配接收以及是否相干处理,将目前的导航接收机归纳为四种类型.其次,在假设码时延估计误差非常小的条件下,分别给出了匹配接收下相干处理和非相干处理时的估计误差以及相互之间的关系;推导了非匹配接收下非相干处理时的估计误差,并讨论了与相干处理时的关系.最后,推导了码时延估计误差的齐夫-扎凯界限,解决了估计误差不满足非常小这一假设条件时的评估.本文提出的评估方法均以导航信号的功率谱密度表示,为信号设计和接收机的研制提供了重要的理论指导,同时也给具体信号的评估带来了极大便利.仿真实验中对新一代典型导航信号的码时延估计误差做了有效评估.     

High resolution time-delay estimation of underwater target geometric scattering

The geometric scatterings carry the information of the shape of an underwater target. While the time-delay of the weak geometric scattering exists in the received signal cannot be obtained accurately by the conventional time-delay estimation methods because of the limit of the main-lobe width and the interferences from the side-lobe. In this paper, we propose a high resolution time-delay estimation (HRTDE) scheme consisting of two steps. Firstly, when a linear-frequency-modulated (LFM) pulse is transmitted by sonar, the dechirping method transforms the geometric scatterings with different time-delays into multiple single-frequency components respectively, in which the frequency of the dechirped signal shows a linear relationship with the time-delay of the geometric scattering. Then the multiple signal classification (MUSIC) algorithm is adopted to increase the spectrum resolution when multiple single-frequency signals exist in the dechirped signal and the frequency interval is smaller than the frequency resolution limit of the Fourier transform. Simulation results show that the main lobe of the proposed scheme is sharper and with less interference from the side-lobe, compared with the conventional time-delay estimation methods. The results from the anechoic pool experiment demonstrate that the proposed scheme achieves a better time-delay estimation performance for the weak geometric scattering generated by the bottom edge of the underwater target model than match filter based methods.     

一种深度学习的立体阵波达方向估计方法

针对常规波束形成主瓣宽且目标分辨能力低的问题,提出一种基于深度卷积神经网络的波达方向估计方法。算法使用常规波束形成计算二维空间功率谱,将预处理后的空间功率谱图输入深度卷积神经网络。该文利用神经网络学习解卷积映射关系,输出主瓣宽度更窄的空间功率谱图,从而实现高分辨率二维波达方向估计。该算法对阵列结构没有限制,适用于立体阵。仿真结果表明该文方法在不同目标个数、快拍数及信噪比参数下均能准确估计目标方向。该文方法目标分辨能力优于常规波束形成方法。在低快拍情况下,目标方向估计误差低于自适应波束形成方法。     

基于倒谱分析的单水听器目标运动参数估计

基于浅海射线声学多途结构,提出了一种具有高稳健性、高精度的单水听器目标运动参估计方法.针对匀速直线运动目标,综合多途时延差和运动学几何关系,构建了目标三维多途时延模型,进而获得目标运动参数与多途时延差的非线性时间映射.研究了典型水声信道的倒谱表达式,提出了利用倒谱提取多途时延差的策略.采用差分进化综合优化手段估计目标运动参数,提高了算法的稳健性.理论及仿真结果表明,倒谱的时间分辨率不受信号带宽的限制,而主要取决于信号类型和信噪比;CW信号的倒谱对多普勒不敏感;参数估计精度主要取决于时延差估计精度和参与差分进化运算的信息量,当包含有最近点信息时参数估计性能较好.水池实验结果进一步验证了方法的正确性和有效性.     

Spectral semi-blind deconvolution with least trimmed squares regularization

A spectral semi-blind deconvolution with least trimmed squares regularization (SBD-LTS) is proposed to improve spectral resolution. Firstly, the regularization term about the spectrum data is modeled as the form of least trimmed squares, which can help to preserve the peak details better. Then the regularization term about the PSF is modeled as L1-norm to enhance the stability of kernel estimation. The cost function of SBD-LTS is formulated and the numerical solution processes are deduced for deconvolving the spectra and estimating the PSF. The deconvolution results of simulated infrared spectra demonstrate that the proposed SBD-LTS can recover the spectrum effectively and estimate the PSF accurately, as well as has a merit on preserving the details, especially in the case of noise. The deconvolution result of experimental Raman spectrum indicates that SBD-LTS can resolve the spectrum and improve the resolution effectively.     

Reconstruction of systems with delayed feedback: II. Application

We apply a recently proposed method for the analysis of time series from systems with delayed feedback to experimental data generated by a laser. The method allows estimating the delay time with an error of the order of the sampling interval, while an approach based on the peaks of either the autocorrelation function, or the time delayed mutual information would yield systematically larger values. We reconstruct rather accurately the equations of motion and, in turn, estimate the Lyapunov spectrum even for high dimensional attractors. By comparing models constructed for different “embedding dimensions” with the original data, we are able to find the minimal faithful model. For short delays, the results of our procedure have been cross-checked using a conventional Takens time-delay embedding. For large delays, the standard analysis is inapplicable since the dynamics becomes hyperchaotic. In such a regime we provide the first experimental evidence that the Lyapunov spectrum, rescaled according to the delay time, is independent of the delay time itself. This is in full analogy with the independence of the system size found in spatially extended systems. Received 17 December 1999     

分布式光纤中的稳健时间延迟估计方法

在分布式光纤传感系统定位中,传统时延估计算法常由于噪声相关性较强而失效。采用一种削弱相关噪声的改进型广义相关法,并针对系统特点,为进一步改善分布式光纤传感定位的准确度与稳定度,提出了一种先对数据按事件信号进行分帧,再采用卡尔曼滤波器对分帧时延估计结果进行跟踪的时延估计方案。系统仿真实验与实际数据测试结果均表明:提出的时延估计方案能够有效抑制强相关性的噪声,提高时延估计的准确度与稳定度。经大量现场测试,本文的方案能够有效地将时延估计误差稳定地控制在0.2个采样间隔以内,能够满足系统实际定位精度要求。     

Beamforming with a reduced sampling rate

The beamforming process requires a high delay resolution to avoid the deteriorating effects of the delay quantization lobes on the image dynamic range and signal to noise ratio. Wideband transducers require delay resolutions in the order of 1/16 the signal period. If oversampling is used to achieve this timing resolution, a huge data volume has to be acquired and processed in real time. This is usually avoided by sampling just above the Nyquist rate and interpolating to achieve the required delay resolution. However this increases the hardware complexity. Baseband sampling has been alternatively proposed with sampling rates as low as the transducer frequency or even lower. This approach uses two A/D converters and processing chains for every channel, thus doubling the hardware requirements. Quadrature sampling can be used instead with a single A/D converter, but the sampling rate must be a multiple of four times the transducer frequency, decreasing the application flexibility. Furthermore, it produces relatively high errors in the detected envelope if wideband transducers are used. This work presents a new approach, the selective sampling technique (SST), which keeps the lowest sampling rate required by the imaging process or the signal bandwidth (whatever is larger) and, at the same time, provides a high delay resolution to keep the highest image dynamic range. The SST is based on a second order sampling process which, differently from the mentioned approaches, does not pose any constraints in the time interval between samples and produce lower errors in the detected envelope. The hardware requirements are low (a single A/D converter and processing chain for every transducer element), working at the lowest data rate compatible with the Nyquist criterion, thus reducing the data bandwidth. Furthermore, the sampling points can be also freely chosen, so that the SST simplify the usually required scan conversion process to a simple linear interpolation easily carried out by software in real-time.     

基于L型延迟阵列调制宽带转换器的信号载频和二维到达角联合估计

针对现有的基于欠采样的频率和二维到达角的联合估计存在结构复杂问题,本文提出了一种基于调制宽带转换器技术的L型延迟阵列接收结构.利用延迟通道与未延迟通道采样值之间的相位差可直接估计载频,进而计算二维到达角,无需额外的参数配对操作,避免了配对步骤引入的误差和复杂度的提升.并结合所提L型延迟阵列结构的特点构造相关矩阵和三线性模型,提出了两种参数估计算法,一种基于旋转不变子空间算法,计算量小,适用于需要实时处理的场景;另一种基于正则分解技术,鲁棒性较好,适用于信噪比较低的应用场景.仿真实验表明该方法能较好地从欠奈奎斯特样本中估计目标的载频和二维到达角参数.     

Estimation of speed of sound in dual-layered media using medical ultrasound image deconvolution

The speed of sound in soft tissues is usually assumed to be 1540 m/s in medical pulse-echo ultrasound imaging systems. When the true speed is different, the mismatch can lead to distortions in the acquired images, and so reduce their clinical value. Previously we reported a new method of sound-speed estimation in the context of image deconvolution. Unlike most other sound-speed estimation methods, this enables the use of unmodified ultrasound machines and a normal scanning pattern. Our approach was validated for largely homogeneous media with single sound speeds. In this article, we demonstrate that sound speeds of dual-layered media can also be estimated through image deconvolution. An ultrasound simulator has been developed for layered media assuming that, for moderate speed differences, the reflection at the interface may be neglected. We have applied our dual-layer algorithm to simulations and in vitro phantoms. The speed of the top layer is estimated by our aforesaid method for homogeneous media. Then, when the layer boundary position is known, a series of deconvolutions are carried out with dual-layered point-spread functions having different lower-layer speeds. The best restoration is selected using a correlation metric. The error level (e.g., a mean error of −9 m/s with a standard deviation of 16 m/s) for in vitro phantoms is found to be not as good as that of our single-speed algorithm, but is comparable to other local speed estimation methods where the data acquisition may not be as simple as in our proposed method.     

Delay-Doppler deconvolution image formation for multiple targets in waveguide environment

The ranges and radial velocities of targets are interesting parameters in the active sonar, which can't be observed directly but can only be estimated. Firstly, by making use of the delay-Doppler model of multi-targets in waveguide multipath environment, one finds that sample cross-ambiguity function is a two-dimensional(2D) convolution of the auto-ambiguity function of the transmitted signal with the generalized target reflectivity density, which is a 2D convolution of the spread function of channel with the reflectivity density as well. Secondly,from the perspective of information theory, an iterative deconvolution algorithm named R-L(Richardson-Lucy) is derived based on minimum Csiszar discrimination criterion. Finally, the blurs caused by both of the transmitted signal and channel are removed by 2D deconvolution of the expectation of sample cross-ambiguity function, 2D image and then parameters of time-delay and Doppler is estimated sequentially. Results of both numerical simulation and sea experimental data processing verify the feasibility and effectiveness of R-L deconvolution algorithm, which effectively improves the resolution and precision of the time delay and Doppler estimation, when compared to the classical match filtering and Wiener filtering.     

Imaging of directional distributed noise sources

This study relates to the acoustic imaging of noise sources that are distributed and strongly directional, such as in turbulent jets. The goal is to generate high-resolution noise source maps with self-consistency, i.e., their integration over the extent of the noise source region gives the far-field pressure auto-spectrum for a particular emission direction. Self-consistency is possible by including a directivity factor in the formulation of the source cross-spectral density. The resulting source distribution is based on the complex coherence, rather than the cross-spectrum, of the measured acoustic field. For jet noise, whose spectral nature changes with emission angle, it is necessary to conduct the measurements with a narrow-aperture array. Three coherence-based imaging methods were applied to a Mach 0.9 turbulent jet: delay-and-sum beamforming; deconvolution of the beamformer output; and direct spectral estimation that relies on minimizing the difference between the measured and modeled coherences of the acoustic field. The delay-and-sum beamforming generates noise source maps with strong spatial distortions and sidelobes. Deconvolution leads to a five-fold improvement in spatial resolution and significantly reduces the intensity of the sidelobes. The direct spectral estimation produces maps very similar to those obtained by deconvolution. The coherence-based noise source maps, obtained by deconvolution or direct spectral estimation, are similar at small and large observation angles relative to the jet axis.     

基于回溯筛选的稀疏重构时延估计算法

针对无线定位中时延估计在小样本(单快拍)、低信噪比条件下需要大量独立分布测量数据问题,提出了一种基于回溯筛选的稀疏重构时延估计算法,实现了单快拍、低信噪比条件下接收信号的精确时延估计.该算法首先建立接收信号的稀疏表示模型,然后基于该模型建立正交观测矩阵,最后在重构算法中引入回溯筛选思想,利用时延与观测矩阵之间的一一对应关系得到时延的无偏估计.对该模型下时延估计的克拉美罗界进行了推导.仿真分析表明,所提方法在单快拍、低信噪比条件下精度远高于求根多重信号分类算法,相比于正交匹配追踪算法,在较小的复杂度代价下性能得到了较大提升.     

雷达定量测量降水的检验“真值”求取方法研究

利用湖南省2013年汛期(4—9月)的高密度区域自动站的雨量数据,引入Cressman逐步订正法求取0.01?×0.01?精细网格的区域降水量,并与距离平方倒数法、距离指数法和距离平方指数法计算的区域降水量进行比较.结果表明,Cressman逐步订正法计算的区域降水量与距离平方倒数法和距离指数法的结果相当,但其空间结构更为精细和准确,更好地反映了雨量站数据的分布特征.交叉验证表明Cressman逐步订正法与原始区域自动站值最为接近,误差绝对值小于0.5 mm的雨量站占总站数的98.71%,误差标准差为0.24 mm.对于0.01?×0.01?精细的空间分辨率而言,Cressman逐步订正法利用高密度的区域自动站数据求得的区域降水量可以用于检验雷达定量估测降水.