Ultrawideband Radar Measurements of Thickness of Snow Over Sea Ice

An accurate knowledge of snow thickness and its variability over sea ice is crucial in determining the overall polar heat and freshwater budget, which influences the global climate. Recently, algorithms have been developed to extract snow thicknesses from satellite passive microwave data. However, validation of these data over the large footprint of the passive microwave sensor has been a challenge. The only method used thus far has been with meter sticks during ship cruises. To address this problem, we developed an ultrawideband frequency-modulated continuous-wave radar to measure the snow thickness over sea ice. We synthesized a very linear chirp signal by using a phase-locked loop with a digitally generated chirp signal as a reference to obtain a fine-range resolution. The radar operates over the frequency range from 2-8 GHz. We made snow-thickness measurements over the Antarctic sea ice by operating the radar from a sled in September and October 2003. We performed radar measurements over 11 stations with varying snow thicknesses between 4 and 85 cm. We observed an excellent agreement between radar estimates of snow thickness with physical measurements, achieving a correlation coefficient of 0.95 and a vertical resolution of about 3 cm. Comparison of simulated radar waveforms using a simple transmission line model with the measurements confirms our expectations that echoes from snow-covered sea ice are dominated by reflections from air-snow and snow-ice interfaces.     

基于单个宽带脉冲的空间目标测距和测速方法

根据运动目标在宽带线性调频脉冲照射下的回波特点,提出了一种采用宽带单个脉冲对运动目标测速和测距的方法。该方法首先对回波信号进行STRETCH处理,然后对处理后的回波进行快速解线性调频,并用ESPRIT方法取代传统的FFT方法,从而大大提高了参数估计精度,实现了采用宽带单个脉冲对运动目标的同时测距与测速。仿真试验表明该方法具有良好的测量精度。     

Improved Correction of Beam Mismatch of the Precipitation Radar After Orbit Boost of the TRMM Satellite

One effort in developing the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) data processing algorithm is to correct the PR received power for mismatched-beam data after the orbit is boosted. The current standard algorithm employs a beam-mismatch correction algorithm based on the rain-echo radar equation (Takahashi's method). However, there remains a need for improving the estimated power of the mismatched-pulse echo returned from the Earth's surface and weak rain because the echo is represented with the surface-echo radar equation and the noise-power level. The error in Takahashi's method causes a negative bias (around 1 dB) in the PR received power near the main lobe clutter. This paper formulates an improved estimate of the mismatched pulse based on the rain-echo radar equation and the surface-echo radar equation for a flat-Earth surface. The improved estimate is then evaluated numerically and experimentally with the actual data obtained by TRMM/PR for observations over the ocean. The consistency of TRMM/PR data sets between preboost and postboost was improved by eliminating the negative bias (around 1 dB) in the PR received power. The mean rain rate near the surface-echo range increases by 10%, and the angle-bin asymmetry of the mean rainfall rate, which is present in the postboost data corrected by Takahashi's method, is resolved.     

Noncooperative target classification using hierarchical modeling ofhigh-range resolution radar signatures

The classification of high-range resolution (HRR) radar signatures using multiscale features is considered. We present a hierarchical autoregressive moving average (ARMA) model for modeling HRR radar signals at multiple scales and use spectral features extracted from the model for classifying radar signatures. First, we show that the radar signal at a different scale obeys an ARMA process if it is an ARMA process at the observed scale. Then, an algorithm to estimate model parameters and power spectral density function at different scales using model parameters at the observed scale is presented. A feature set composed of spectral peaks is extracted from the estimated spectral density function using multiscale ARMA models. For HRR radar signature classification, multispectral features extracted from five different scales are used, and a minimum distance classifier with multiple prototypes is used to classify HRR data. The multiscale classifier is applied to two HRR radar data sets. Each data set contains 2500 test samples and 2500 training samples in five classes. For both data sets, about 95% of the radar returns are correctly classified     

Ultrawide-band coherent processing

In this paper, we develop an approach for estimating the ultrawide-band (UWB) radar signature of a target by using sparse subband measurements. First, we determine the parameters of an appropriate signal model that best fits the measured data. Next, the fitted signal model is used to interpolate between and extrapolate outside of the measurement subbands. Standard pulse-compression methods are then applied to provide superresolved range profiles of the target. The algorithm can automatically compensate for lack of mutual coherence between the radar subbands, providing the potential for UWB processing of real-world radar data collected by separate wide-band radars, because the processing preserves the phase distribution across the measured and estimated subbands, extended coherent processing can be applied to the UWB compressed radar pulses to generate superresolved radar images of the target. Applications of this approach to static test range and field data show promising results     

Moving target feature extraction for airborne high-range resolutionphased-array radar

We study the feature extraction of moving targets in the presence of temporally and spatially correlated ground clutter for airborne high-range resolution (HRR) phased-array radar. To avoid the range migration problems that occur in HRR radar data, we first divide the HRR range profiles into low-range resolution (LRR) segments. Since each LRR segment contains a sequence of HRR range bins, no information is lost due to the division, and hence, no loss of resolution occurs. We show how to use a vector auto-regressive (VAR) filtering technique to suppress the ground clutter, Then, a parameter estimation algorithm is proposed for target feature extraction. From the VAR-filtered data, the target Doppler frequency and the spatial signature vectors are first estimated by using a maximum likelihood (ML) method. The target phase history and direction-of-arrival (DOA) (or the array steering vector for an unknown array manifold) are then estimated from the spatial signature vectors by minimizing a weighted least squares (WLS) cost function. The target radar cross section (RCS)-related complex amplitude and range-related frequency of each target scatterer are then extracted from the estimated target phase history by using RELAX, which is a relaxation-based high-resolution feature extraction algorithm. Numerical results are provided to demonstrate the performance of the proposed algorithm     

Estimation of raindrop size distribution from spaceborne Radar observations

The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar uses surface reference method to estimate the attenuation encountered in the observation of radar reflectivity. The cumulative attenuation estimated from the surface reference method can be distributed along the radar range using a power law relation between the specific attenuation (k) and reflectivity factor (Z). A physical interpretation of the variability in the k-Z relation can be provided with the normalized drop size distributions. This paper describes an algorithm to estimate the drop size distribution (DSD) parameters from the measured attenuation and reflectivity values obtained from TRMM precipitation radar observations. Coincident data collected with ground polarimetric radar during the TRMM field campaigns is used to cross-validate the estimates of drop size distribution parameters obtained from the TRMM precipitation radar. The results of cross validation show fairly good agreement with the drop size distribution parameters retrieved from TRMM precipitation radar and the ground-radar-based estimates. The algorithm is subsequently used to generate monthly global maps of DSD. The global distribution of DSDs is critically important for development of retrieval algorithms used by the Global Precipitation Mission Radiometers.     

Scattering-Based Tomography for HRR and SAR Prediction

This paper introduces a method for predicting HRR radar signatures and SAR images by creating a parametric three-dimensional scattering model from existing measured or model-based HRR signatures and/or SAR images. The method identifies potential three-dimensional persistent scatterers and estimates their scattering patterns. The results are parametric HRR signature and SAR image reconstruction functions of range, azimuth, and elevation.The modeling is accomplished through a scattering-based tomography technique. This technique localizes potential scatterers by using a filtered back-projection algorithm for the inverse radon transform. Once found, potential scatterers may then have their two-dimensional (azimuth and elevation) scattering patterns parameterized through the use of a truncated spherical harmonic series.Results using the reconstructions from HRR data are presented. A M109 model is reconstructed based on HRR signatures. The model allows us to predict what the vehicle would look like from any arbitrary orientation using SAR. Finally an M548 vehicle is modeled using 26 measured HRR signatures. The model is shown to be better than the synthetic model data. Additionally we show that the new model results can be combined with the synthetic data to provide a better target model for signature matching.     

一种基于单帧数据的步进频信号运动补偿方法

介绍了频率步进雷达中多普勒效应对距离像的影响,根据频率步进雷达中常见运动补偿方法的优缺点,提出了一种仅利用单帧数据即可实现速度估计和补偿的方法,为了提高该方法的抗噪声性能,采取对算法进行迭代运算得出有效速度估计值的策略.理论分析和计算机仿真结果表明,该方法只需几次迭代(一般为3次或4次)即可得出有效速度估计值;该算法具有可行性.并兼有测速精度较高、运算量较小、抗噪声性能较强的优点.     

基于SFCW雷达时间－距离像的摆动目标微动特征提取

建立频率步进连续波雷达摆动点目标回波模型,推导得出摆动目标高分辨距离像,研究距离像周期性变化规律,提出基于时间－距离像的摆动目标微动特征提取思路。针对幅度峰值搜索法对微摆动周期估计误差较大的问题,提出结合数据预处理的幅度峰值搜索法和幅度阈值检测法等两种改进算法。仿真实验表明,在信噪比高于-10 dB时,结合数据预处理的幅度峰值搜索法和幅度阈值检测法能够有效估计摆动目标距离、摆动幅度及摆动周期等参数,此时摆动幅度估计值是对其真实值在雷达视线方向上的投影值的估计。改进算法对目标距离和摆动幅度的估计精度与幅度峰值搜索法相同,对摆动周期的估计精度远远高于幅度峰值搜索法,可分别达到和优于采样周期的数量级。本文提出的改进算法可扩展应用于圆周旋转等周期性运动目标的微动特征提取。      

一种主瓣干扰环境下的雷达目标参数"同维"稀疏估计方法

主瓣干扰对抗一直以来是雷达领域的难题之一，给雷达的探测、跟踪和识别带来了严重威胁.对此，本文提出了一种主瓣干扰环境下的雷达目标参数"同维"稀疏估计方法，可有效抑制主瓣干扰并估计目标距离、角度参数.所提方法首先对接收信号进行阻塞矩阵预处理，可在抑制主瓣干扰的同时保持目标回波在各阵元之间的相位关系，即保留了目标的角度信息；然后对预处理后的数据进行空域波束合成并脉压，可估计目标的距离参数信息；最后，根据得到的目标距离估计，截取预处理数据中目标附近的数据，并对其进行稀疏恢复估计目标角度参数.所提方法即可应用于面阵，也可应用于线阵，其优势在于可以在空域任何一维上抑制主瓣干扰，并同时估计目标在空域两维上的角度.尤其是当目标与干扰的某一维空域角度相同时，所提方法仍然可以同时估计目标的方位、俯仰角.     

机载非正侧阵雷达自适应子空间方法

机载非正侧阵雷达使杂波具有距离非平稳特性且传统的空时自适应方法性能下降严重。为了解决这个问题,该文提出一种自适应的子空间方法。该方法首先利用曲线拟合估计构型参数,然后利用估计的构型参数计算杂波子空间,最后将数据向杂波子空间对应的正交补空间进行投影来抑制杂波。仿真实验结果表明,该方法可以取得较好的参数估计精度与杂波抑制性能。     

基于封闭式鲁棒中国余数定理的两目标距离估计算法

工作在高脉冲重复频率（Pulsed Repetition Frequency, PRF）模式下的脉冲多普勒（Pulse Doppler, PD）雷达具有复杂气象杂波和强地杂波背景下检测运动目标的能力,但是远距离目标检测存在距离模糊问题。传统的解距离模糊算法大都采用参差重频模式下的中国余数定理（Chinese Remainder Theorem, CRT）,但是由于多目标的视在距离与目标的对应关系事先未知,对基于中国余数定理算法进行距离估计带来困难。该文提出一种基于封闭式鲁棒中国余数定理的两个目标距离估计的方法,该方法无需考虑视在距离与目标的对应关系,在视在距离存在误差的情况下,利用封闭式的简单解析方法快速准确地重构出两个目标的真实距离。理论分析和仿真结果表明,该文所提方法可以高效地实现高PRF雷达两个远距离目标的距离估计。      

雷达目标一维距离像计算仿真研究

在雷达目标识别研究中,获取有效的雷达目标特征信号非常重要。通过计算机仿真来获取雷达目标一维距离像。仿真时先对目标外形进行三角面元逼近,利用面元法得到目标随频率变化的R苍值,进行变换后得到目标的一维距离像。给出了一类舰船目标的仿真实验。结果表明该方法在一定程度上可以较好地模拟复杂目标的雷达特征信号。最后指出了需要进一步研究的问题。     

基于交替投影的DOA估计方法及其在米波雷达中的应用

由于低仰角目标回波中存在多径信号,使得米波雷达难以对低仰角目标进行高度测量,为此该文提出一种适用于多径信号情况下的波达方向估计的迭代方法。该方法将回波信号的相关矩阵,在各个信号子空间中交替投影,该方法可以同时对直达波和反射波进行精确的波达方向估计,并可以有效地对米波雷达中的低仰角低空目标进行高度测量。计算机仿真和某米波雷达实测数据的处理结果证实了该方法的有效性。Monte-Carlo试验结果表明在低仰角低空测高时,该方法具有比时空级联最大似然方法更好的性能。     

Fusion of satellite active and passive microwave data for sea icetype concentration estimates

Young first-year sea ice is nearly as important as open water in modulating heat flux between the ocean and atmosphere in the Arctic. Just after the onset of freeze-up, first-year ice is in the early stages of growth and will consist of young first-year and thin ice. The distribution of sea ice in this thickness range impacts heat transfer in the Arctic. Therefore, improving the estimates of ice concentrations in this thickness range is significant. The NASA Team Algorithm (NTA) for passive microwave data inaccurately classifies sea ice during the melt and freeze-up seasons because it misclassifies multiyear ice as first-year ice. We developed a hybrid fusion technique for incorporating multiyear ice information derived from synthetic aperture radar (SAR) images into a passive microwave algorithm to improve ice type concentration estimates. First, we classified SAR images using a dynamic thresholding technique and estimated the multiyear ice concentration. Then we used the SAR-derived multiyear ice concentration to constrain the NTA and obtained an improved first-year ice concentration estimate. We computed multiyear and first-year ice concentration estimates over a region in the eastern-central Arctic in which field observations of ice and in situ radar backscatter measurements were performed. The fused estimates of first-year and multiyear ice concentration appear to be more accurate than NTA, based on ice observations that were logged aboard the US Coast Guard Icebreaker Polar Star in the study area during 1991     

Reconnaissance with slant plane circular SAR imaging

This paper presents a method for imaging from the slant plane data collected by a synthetic aperture radar (SAR) over the full rotation or a partial segment of a circular flight path. A Fourier analysis for the Green's function of the imaging system is provided. This analysis is the basis of an inversion for slant plane circular SAR data. The reconstruction algorithm and resolution for this SAR system are outlined. It is shown that the slant plane circular SAR, unlike the slant plane linear SAR, has the capability to extract three-dimensional imaging information of a target scene. The merits of the algorithm are demonstrated via a simulated target whose ultra wideband foliage penetrating (FOPEN) or ground penetrating (GPEN) ultrahigh frequency (UHF) radar signature varies with the radar's aspect angle.     

雷达目标高分辨距离像的物理统计建模方法

根据雷达目标高分辨距离像的特点．提出了一种新颖的对高分辨距离像的统计建模方法：采用物理统计非高斯模型对高分辨距离像建模。介绍了该模型及其参数的物理意义，阐述了两种模型参数估计方法。应用实测的多类目标数据对该方法进行了验证。结果表明，该建模方法能反映距离像的结构特点．达到了令人满意的建模精度.     

A Compact Direction-Finding Antenna for HF Remote Sensing

A compact four-element antenna, along with a numerical direction-finding algorithm, is analyzed using computer simulations that model sea-echo data obtained with an HF pulsed Doppler radar. The algorithm consists of closed-form expressions and is capable of deriving the angles-of-arrival for one or two signals impinging upon the antenna. Errors associated with the calculated angles are presented as a function of signal-to-noise ratio. In addition, it is demonstrated that preaveraging antenna voltages over independent data samples can decrease the angle errors and extend the range of the radar.     

运动点目标空间定位算法研究

提出了一种基于冲激雷达体制的运动点目标空间定位算法,该算法针对冲激雷达的特点,采用距离门等效采样的方式采集各个发射脉冲的回波数据,通过对采集到的数据进行相关处理得到点目标经过各个距离门时不同接收天线间的距离差,并利用TDOA方法实现点目标在各定位点的空间定位。通过对目标运动模型的建立,可进一步通过Kal- man平滑滤波的方法提高运动点目标坐标的估计精度,仿真结果表明该定位算法具有较高的定位精度。