12.9m高分辨率合成孔径激光雷达成像

报道了一个条带模式合成孔径激光雷达(SAL)实验室高分辨率成像结果。以0.5 mm×0.5 mm的等效收发口径,在一个12.9 m距离上,实现了高分辨率SAL成像,获得了照片级的高质量图像。图像的方位合成孔径分辨率超过真实口径衍射极限分辨率的100倍。详细给出了合作目标和漫反射目标的距离压缩像、方位聚焦像和相位梯度自聚焦(PGA)处理像。实验数据展现了清晰的SAL图像形成过程,显示出了各处理步骤的典型聚焦效果。实验结果演示了PGA在SAL图像处理中的稳健聚焦能力,多次迭代能较大幅度地提高成像质量。     

天基合成孔径激光雷达成像理论初步

合成孔径激光雷达(SAL)具有成像距离远、分辨率高、速度快等特点,在天基空间目标成像领域有重要的应用前景。针对天基SAL成像中回波信号弱、噪声大、成像质量差等问题,提出在交会点附近连续长时间观测的思路。基于简单假设,建立采用光学外差探测的天基SAL成像理论数学模型,获得回波数据方程,给出成像处理流程、成像分辨率和图像信噪比,数学仿真了不同信噪比下的天基SAL空间目标成像。理论分析和仿真成像结果表明:当回波数据信噪比高时,任何子段数据均可形成空间目标的高分辨率图像;当回波信号微弱、数据信噪比低时,采用连续长时间观测数据形成目标子图像,将所有子图像进行叠加,提升了目标图像信噪比,改善了成像质量。     

大气湍流下合成孔径激光雷达成像数值模拟及PGA补偿

为研究大气湍流对合成孔径激光雷达(SAL)的成像影响,采用谱反演法对符合Kolmogorov谱的大气随机相位屏进行了数值模拟,给出了单层及多层叠加的随机相位屏图像;然后以多层随机相位屏叠加方式模拟实际大气湍流,计算了无湍流、弱湍流、中等湍流和强湍流等情况下理想机载单站聚束式SAL对点目标以及扩展目标的成像,模拟成像表明大气湍流对SAL成像的方位分辨率有严重影响,湍流越强,图像方位向分辨率越差;针对湍流造成的SAL图像方位向分辨率降低,采用相位梯度自聚焦(PGA)算法对SAL图像进行了方位向补偿,结果有效地改善了图像的聚焦效果,提高了成像质量。     

PGA算法在条带式SAS场景目标成像中的应用

本文针对条带式合成孔径声呐(SAS)对场景目标成像应用中面临的方位向残余相位误差导致成像质量降低的问题,探讨了相位梯度自聚焦(PGA)算法在条带式SAS成像方位向相位误差估计和补偿中的应用方法,通过自适应的选点及窗宽估计处理以提高算法对场景目标的适应性,最后通过对场景目标成像的实际湖试数据进行处理和分析,结果验证了该算法改善条带式SAS对场景目标成像质量的有效性。     

一种机载合成孔径激光雷达相位误差补偿方法

准确理解大气湍流扰动相位对光束传输特性的影响机制,并以此为基础发展有效的相位误差补偿算法是实现合成孔径激光雷达(SAL)高质量成像的关键之一.从激光光束的相位结构函数入手,提出了一种新的大气湍流相位屏产生方法--结构函数法,建立了满足Kolmogorov统计规律的大气湍流数值模型,计算了不同强度湍流作用下机载SAL的成像结果.通过将其与秩一相位估计法联合使用,克服了秩一法对初始值敏感的缺点,提高了补偿算法的精度和效率.实验表明,与谱反演法相比,结构函数法的计算结果更接近于理论值,同时计箅复杂度由O(N2)降至O(N).改进的秩一法能够较为有效地改善一定强度范围内大气湍流引起的SAL图像失真,而且补偿后图像的信噪比相比传统的秩一法提高了大约5 dB,计算时间也缩短了约30%.     

基于迭代的傅里叶望远镜图像重构方法

为了提高最终图像的质量,结合传统的直接重构算法和相位重构算法,提出了一种基于迭代的傅里叶望远镜图像重构方法。对反演得到的傅里叶频谱进行逆傅里叶变换得到直接重构图像,取直接重构图像的阈值图像作为相位重构算法的初始输入,通过迭代能够获得质量更高的图像。成像仿真实验结果表明,成像信噪比为50倍时,与直接重构图像相比,迭代重构图像斯特列尔比从0.82提高到0.88,峰值信噪比从17dB提高到19dB;在成像信噪比为100倍时,迭代重构图像斯特列尔比从0.89提高到0.93,峰值信噪比从20dB提高到22dB。     

相干场成像全相位目标直接重构法

回波信号处理和目标重构算法是相干场成像中的核心数据处理技术, 直接影响系统的成像质量. 基于全相位谱分析理论, 提出一种新的系统融合处理算法, 对接收端回波信号直接提取全相位谱相位及幅值信息实现目标图像重构, 能够有效抑制各种因素带来的频率误差. 经室外实验系统验证, 成像能力大大优于传统重构算法, 重构目标分辨率接近理论极限值.     

机载合成孔径激光雷达全孔径成像算法

合成孔径激光雷达(SAL)是合成孔径与激光雷达的结合体。由于SAL的工作波长较短,可以在短时间内实现高分辨率成像,近年来发展较快。但短波长也会带来其他问题,对于机载SAL,其波长比载机振动幅度小1～2个数量级,所以载机的振动会给回波带来较大的相位误差,传统的惯导系统很难达到激光波长级的定位精度,需要进行基于数据的自聚焦才能实现SAL成像。针对这一问题,提出一种利用最小熵自聚焦(MEA)和deramp结合的全孔径成像算法,并利用该算法对SAL实测数据进行了成像处理,成像结果证明了该算法的有效性。     

太赫兹逆合成孔径雷达相位误差分析和补偿方法

通过对太赫兹逆合成孔径雷达(THz-ISAR)成像原理进行分析,构造目标回波距离维相位误差的多项式表示形式,提出了基于启发式最小熵搜索的二次相位误差校正方法和基于距离维自聚焦的三次及三次以上相位误差校正方法,校正了THz-ISAR回波信号距离维的相位误差,进而消除THz-ISAR一维距离像和二维成像结果中的散焦和展宽现象。理论分析和仿真实验结果都表明该方法能够有效补偿目标回波距离维相位误差,提高一维距离像和二维成像的聚焦效果。     

机载合成孔径激光雷达相位误差补偿研究

为了研究大气湍流对合成孔径激光雷达(SAL)成像的影响,基于Monte-Carlo随机因子,对满足Kolmogorov统计规律的大气湍流相位屏进行数值模拟,计算了不同湍流、不同波长情况下的机载SAL成像结果,数值分析了不同斜距、不同波长条件下合成孔径长度与大气相干长度比值随大气湍流强度的变化关系。结果表明大气湍流效应严重影响了SAL的方位向成像,随着湍流强度的增大,SAL图像散焦越来越严重,直至目标无法分辨。同一湍流强度下,光束波长越长,SAL成像效果越好。对于湍流效应造成的SAL图像失真,采用改进的秩一相位误差估计(IROPE)法对SAL图像进行补偿,当大气相干长度大于实孔径长度时,IROPE算法能够有效改善图像的聚焦效果,提升SAL成像分辨率。     

机械抖动激光陀螺的高分辨率信号处理

 机械抖动激光陀螺（MDRLG）信号是两路相位差为π/2的正弦拍频信号,一般采用4倍频鉴相输出计数脉冲,利用FIR滤波和抖动剥除等方法解调抖动信号,从而得到外界输入的角速度信息。高速采集MDRLG信号,并细分为相位依次相差π/16的16路信号,实现MDRLG的8倍频、16倍频和32倍频鉴相输出。输出角速率的均方差随着倍频数的提高而减小,信号处理的分辨率得到提高。实验测试和Allan方差分析表明：32倍频时的量化误差Q从4倍频鉴相时的0.327″减小到0.170″,增加MDRLG信号鉴相的倍频数可以减小量化误差。在对MDRLG信号进行抖动剥除解调时,由于量化误差是主要误差源之一,高分辨率信号处理能够有效提高MDRLG角速度测量的精度。     

高精度多脉冲激光测距回波检测技术

针对远距离激光测距机回波信号脉宽强度特征和噪声的统计特性,提出了一种高精度多脉冲激光测距机的回波信号检测技术。采用时钟移相分配方式实现了400 MHz高速信号采集及数字化处理,提高了回波脉冲的检测精度。采用ARM嵌入式高速核处理器进行数据算法处理,完成了滤波降噪、自适应门限检测和多帧相关检测等功能,使回波信噪比提高了7.6 dB,达到远距离精确获取目标距离信息的目的。     

CO2激光成像雷达距离分辨率测距精度的分析与实验研究

分析了脉冲外差体制CO₂激光成像雷达系统的目标距离分辨率、测距精度和误差的主要来源.对于单个光脉冲测距来讲,信噪比(SNR)起伏引起的探测误差、脉冲前沿触发等概率分布以及脉冲建立时间的随机性等是激光脉冲外差测距的主要随机误差,其它随机误差在数量级上可忽略不计.同时利用现有的CO₂激光脉冲外差探测系统,进行了远目标测距对比实验,观测到了2355 m目标脉冲回波信号,并精确测量出CO₂光脉冲飞行的往返时间,该实验数据可用做系统误差的校正和补偿.     

激光相干场成像散斑噪声复合去噪方法

噪声是影响激光相干场高分辨成像系统像质的重要因素,激光相干场成像系统既受背景光加性噪声影响,又受激光乘性散斑噪声影响.为解决激光相干场成像系统受激光乘性散斑噪声和背景光加性噪声叠加引起的成像像质退化效应问题,从噪声抑制角度提高激光相干场系统高分辨成像像质,研究建立了激光散斑乘性噪声和背景光加性噪声对大气下行链路激光回波场信号影响干扰模型,并基于该模型提出了一种基于同态滤波和稀疏基追踪级联复合去噪算法.首先基于同态滤波理论将激光乘性散斑噪声转化为加性噪声,再由高通滤波器滤除散斑噪声,最后采用基追踪稀疏理论方法抑制背景光等加性噪声对像质的影响.研究表明,较现有单一去噪方法,该级联复合去噪方法可一次性消除激光乘性散斑噪声和背景加性噪声两种不同性质的噪声,有效改善了激光相干场成像质量.     

Scanning time efficient slinky for non-contrast MRA at low field.

To eliminate slab boundary artifact (SBA) for non-contrast multi-slab three-dimensional time-of-flight magnetic resonance angiogram (3D TOF MRA), we have previously developed a novel technique, termed SLINKY (Sliding Interleaved kY) acquisition in which a thin slab continuously "walks" along the z-axis while data are acquired in an interleaved fashion along the kY-axis. It has been demonstrated in our earlier works that SLINKY can suppress the SBA without any assumption of blood flow behavior, such as velocity or direction. At the same time, SLINKY keeps the same SNR as conventional multiple overlapping thin slab acquisition (MOTSA). Yet, this method is sensitive to any phase error along the ky axis. In our earlier application of SLINKY, we used navigator echoes to measure and correct the phase errors along the kY axis. The cost of using navigator echo collection is an increase in the imaging time. We therefore propose an improved SLINKY technique which does not use navigator echo collection for correcting phase errors, reducing the imaging time while keeping the same suppression of slab boundary artifacts. The present study demonstrates that by using a specifically designed RF pulse, the navigator echo collection can be avoided without incurring any extra ghosting or SNR reduction in the reconstructed images.     

A realization of digital wireless transmission for MRI signals based on 802.11b

In this paper, a digital wireless transmission system based on 802.11b standard for magnetic resonance imaging (MRI) application is designed and built for the first time to eliminate the interference aroused by coil array cables. The analysis shows that the wireless receiver has a very high sensitivity to detect MRI signals. The modulation technique of differential quadrature phase shift keyed (DQPSK) can be applied to MRI data transmission with rate of 2 Mbps and bandwidth of 2 MHz. The bench test verifies that this wireless link has a dynamic range over 86 dB supporting up to 3 T MRI system data transmission. The 2D spin echo imaging of phantom is performed and the SNR of the image obtained by the wireless transmission can be comparable with that got by the coaxial cables.     

A wavelet-based method for improving signal-to-noise ratio and contrast in MR images

Magnetic resonance (MR) images acquired with fast measurement often display poor signal-to-noise ratio (SNR) and contrast. With the advent of high temporal resolution imaging, there is a growing need to remove these noise artifacts. The noise in magnitude MR images is signal-dependent (Rician), whereas most de-noising algorithms assume additive Gaussian (white) noise. However, the Rician distribution only looks Gaussian at high SNR. Some recent work by Nowak employs a wavelet-based method for de-noising the square magnitude images, and explicitly takes into account the Rician nature of the noise distribution. In this article, we apply a wavelet de-noising algorithm directly to the complex image obtained as the Fourier transform of the raw k-space two-channel (real and imaginary) data. By retaining the complex image, we are able to de-noise not only magnitude images but also phase images. A multiscale (complex) wavelet-domain Wiener-type filter is derived. The algorithm preserves edges better when the Haar wavelet rather than smoother wavelets, such as those of Daubechies, are used. The algorithm was tested on a simulated image to which various levels of noise were added, on several EPI image sequences, each of different SNR, and on a pair of low SNR MR micro-images acquired using gradient echo and spin echo sequences. For the simulated data, the original image could be well recovered even for high values of noise (SNR approximately 0 dB), suggesting that the present algorithm may provide better recovery of the contrast than Nowak's method. The mean-square error, bias, and variance are computed for the simulated images. Over a range of amounts of added noise, the present method is shown to give smaller bias than when using a soft threshold, and smaller variance than a hard threshold; in general, it provides a better bias-variance balance than either hard or soft threshold methods. For the EPI (MR) images, contrast improvements of up to 8% (for SNR = 33 dB) were found. In general, the improvement in contrast was greater the lower the original SNR, for example, up to 50% contrast improvement for SNR of about 20 dB in micro-imaging. Applications of the algorithm to the segmentation of medical images, to micro-imaging and angiography (where the correct preservation of phase is important for flow encoding to be possible), as well as to de-noising time series of functional MR images, are discussed.     

脉冲激光测距回波信号时间选通处理技术

为了降低高重频脉冲激光测距回波信号的误识别率，提高测距性能，对高重频脉冲激光测距回波信号调理技术进行深入研究。采用FPGA作为主控芯片，产生激光调制脉冲，并根据被测距离3.33 μs～33.33 μs时间选通方波信号，驱动开关芯片产生与量程关联的时间波门，有效滤除脉冲回波中的干扰脉冲，该方法改进了常规脉冲激光测距信号处理系统的自动增益控制环节。测试实验结果表明:在脉冲回波信号60 dB的动态范围内，可有效滤除回波信号中引入的干扰脉冲，极大地降低了干扰脉冲误识别造成粗大误差的可能性。该方法可推广应用于脉冲激光测距信号处理系统，使系统测距精度提高12.6%。     

Acceleration target detection based on LFM radar

In radar systems, the echo signal caused by an accelerated target can be similarly considered as linear frequency modulation (LFM) signal. In high signal-to-noise ratio (SNR), discrete polynomial-phase transform (DPT) algorithm can be used to detect the echo signal, as it has low computation complexity and high real-time performance. However, in low SNR, the DPT algorithm has a large mean square error of the rate of frequency modulation and a low detection probability. In order to detect LFM signal in low SNR, this paper proposes a detection method, segment discrete polynomial-phase transform (SDPT), which means, at first, dividing the whole echo pulses into several segments with same duration in time domain, and then, using coherent accumulation method of DFT to segments, at last, processing this signal with DPT in intra-segment. In the case of a large number of segments, the SDPT can improve the output SNR. In addition, in a certain SNR, to the target signal with big sampling interval, large acceleration and less segments, this paper proposes an algorithm to detect the LFM signal generated from the combination of an improved DPT (IDPT) and fractional Fourier transform (FRFT). The output SNR of this algorithm is connected with the length of time delay. In the simulation, when the length of the time delay is 0.2 N, the output SNR is 2.5 dB more than that which results from directly using DPT. Finally, the detection performance and algorithm complexity of the proposed algorithm were analyzed, and the simulated and measured data verify the effectiveness of the algorithm.