A new CFAR sidelobe canceler algorithm for radar

Signal or target detection is sometimes complicated by the presence of strong interference. When this interference occurs mainly in the sidelobes of the antenna pattern, a solution to this problem is realized through a sidelobe canceler (SLC) implementation. Since the false-alarm probability is a system parameter of special importance in radar, an interference-canceling technique for radar application should maintain the false-alarm probability constant over a wide range of incident interference power. With the requirements of sidelobe interference cancellation and constant false alarm rate (CFAR), a new algorithm for radar detection in the presence of sidelobe interference is developed from the generalized likelihood ratio test of Neyman-Pearson. In this development, the received interference is modeled as a nonstationary but slowly varying Gaussian random process. Cancellation of the sidelobe interference is based upon a `synchronous' estimate of the spatial covariance of the interference for the range gate being tested. This algorithm provides a fixed false-alarm rate and a fixed threshold which depend only upon the parameters of the algorithm     

A multiresolution approach to discrimination in SAR imagery

We develop and test a new algorithm for discriminating man-made objects from natural clutter in synthetic-aperture radar (SAR) imagery. This algorithm exploits characteristic variations in speckle pattern as image resolution is varied from course to fine. We model these variations as an autoregression in scale, and then use the autoregressive model to define a multiresolution log-likelihood ratio discriminant. We incorporate this discriminant into the existing Lincoln Laboratory SAR system for automatic target recognition (ATR), and test the augmented system by applying it to millimeter-wave SAR imagery having 0.3 m resolution and representing 56 square kilometers of terrain. At a probability of detection of 0.95, the addition of the multiresolution discriminant reduces the number of natural-clutter false alarms by a factor of six.     

A Sequential Detector

The PRSD detector improves radar performance by controlling the distribution of energy in space, thus making a radar adaptive to its environment. An increase in performance over classical detectors may be realized in any of several ways: 1) greater maximum range; 2) smaller minimum detectable targets; 3) higher data rates; 4) lower average transmitted power, which allows smaller size and weight of equipment. The model of the PRSD detector described herein was tested with a semi-agile beam radar, and gave measured field performance improvement (for this particular radar) equivalent to an S/N increase ranging from 5 to 22 dB with a mean of 9.5 dB. This increase is greater than the 5-dB improvement predicted for the system in a white noise environment because many of the field tests were at locations subjected to heavy interference. The PRSD detector was extremely effective reducing the interference. In this paper, we will briefly review the theory of operation, describe the equipment and the method of test, and present experimental data. The data presented here are essential to a complete understanding of sequential detection since a rigorous theory encompassing multiple range bin radar has not been developed at this time. Finally, an extensive bibliography is appended.     

Improved algorithm for estimating pulse repetition intervals

This paper presents an improved algorithm for estimating pulse repetition intervals (PRIs) of an interleaved pulse train which consists of several independent radar signals with different PRIs. The original version of this algorithm is a complex-valued autocorrelation-like integral, which leads to a kind of PRI spectrum wherein the locations of the spectral peaks indicate the PRI values. The original algorithm, however, has a serious drawback in that it is vulnerable to timing jitter (PRI jitter). We analyze the cause of this vulnerability and propose an improved algorithm using overlapped PRI bins which have shifting time origins. The improved algorithm has proven to be quite effective in obtaining the PRI spectrum for jittered pulse trains, which enables detection of mean PRIs by thresholding     

A novel target detection approach based on adaptive radar waveform design

To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.     

有限姿控能力的低RCS微小卫星姿态实时规划

 为提高在轨微小卫星使用效能及生存能力,提出一种受姿控能源消耗及驱动能力约束的低雷达散射截面（RCS）微小卫星姿态实时规划算法。算法应用曲面像素法、时域有限差分法及假设检验,在三维空间内对微小卫星的RCS及雷达探测水平进行建模,并结合雷达分布模型构建了相应的威胁评估函数及规划代价评估函数。同时,为提高算法的实时性能,采用了粒子群优化(PSO)算法以降低计算复杂度。仿真结果表明,在有限计算量的基础上,算法能够以较小规划代价有效降低卫星威胁方向的RCS及雷达探测概率,满足对微小卫星飞行姿态实时规划的需要。     

A branch-and-bound algorithm applied to optimal radar search pattern

In the article, the radar acquisition problem, e.g. the determination of a directional energy allocation sequence, is studied. The radar search pattern goal is the detection of a moving target whose initial location is approximately known. We have turned towards the general search theory where the observer allocates indivisible search efforts while the target presence probability spreads due to its dynamics. A few years ago, a Branch and Bound algorithm was proposed to determine the optimal sequence for a conditionally deterministic target. This operational research algorithm supposes a negative exponential detection function and a one over N detection logic, meaning that the target is declared detected if it has been detected once over a horizon of N looks. We have applied it to a narrow-beam tracking radar attempting to acquire a ballistic target. Non-trivial search patterns, such as expanding-contracting spirals, are obtained.     

Application of frequency correlation function to radar target detection

Analysis of high-resolution 35 GHz synthetic aperture radar (SAR) imagery of terrain reveals that when point targets, such as vehicles, are viewed at angles close to grazing incidence, they are often difficult to distinguish from tree trunks because the radar cross section (RCS) intensities of the vehicles are comparable to the upper end of the RCS exhibited by tree trunks. To resolve the point target/tree trunk ambiguity problem, a detailed study was conducted to evaluate the use of new detection features based on the complex frequency correlation function (FCF). This paper presents an analytical examination of FCF and its physical meaning, the results of a numerical simulation study conducted to evaluate the performance of a detection algorithm that uses FCF, and the corroboration of theory with experimental observations conducted at 35 and 95 GHz. The FCF-based detection algorithm was found to correctly identify tree trunks as such in over 90% of the cases, while exhibiting a false alarm rate of only 3%.     

雷达检测性能试验等效推算方法

 雷达检测性能是雷达最基本、最重要的性能,雷达检测性能试验是雷达试验的重要内容。由于各种原因,针对雷达的系统级原型试验常常难以开展或者只能极少量地开展,通常只能通过进行大量等效试验来辅助雷达性能的鉴定评估工作。本文针对缺乏原型试验条件下的雷达检测性能评估问题,提出了一种基于试验数据分析的雷达检测性能等效推算方法。首先给出了等效试验与原型试验之间的差异性度量方法,它是等效推算和性能评估的基础;接着对存在原型试验条件下的等效推算方法进行了研究;而后针对通常无法进行原型试验的实际情况,提出了一种基于预测模型和仿真试验相结合的零子样原型试验条件下的等效推算方法;最后通过仿真实例验证了本文方法的合理性和可行性。     

Moving target localization in distributed MIMO radar with transmitter and receiver location uncertainties

In this paper, the problem of moving target localization from Bistatic Range(BR) and Bistatic Range Rate(BRR) measurements in a Multiple-Input Multiple-Output(MIMO) radar system having widely separated antennas is investigated. We consider a practically motivated scenario,where the accurate knowledge of transmitter and receiver locations is not known and only the nominal values are available for processing. With the transmitter and receiver location uncertainties,which are usually neglected in MIMO radar systems by prior studies, taken into account in the measurement model, we develop a novel algebraic solution to reduce the estimation error for moving target localization. The proposed algorithm is based on the pseudolinear set of equations and two-step weighted least squares estimation. The Cramer-Rao Lower Bound(CRLB) is derived in the presence of transmitter and receiver location uncertainties. Theoretical accuracy analysis demonstrates that the proposed solution attains the CRLB, and numerical examples show that the proposed solution achieves significant performance improvement over the existing algorithms.     

Low-cost technology for multimode radar

A flexible test bed radar architecture is described which includes an integrated RF electronics package that can support multiple radar applications, including surveillance, fire control, target acquisition, and tracking. This type of architecture can significantly reduce the cost, power, size, and weight of electronics on future weapon delivery platforms. The Army Research Laboratory (ARL) is developing technology to support multimode radar requirements. These requirements include the detection and location of moving or stationary low radar cross section targets in heavy ground clutter and the classification and/or recognition of these targets. We address these requirements with commercial-off-the-shelf (COTS) products and the integration of several enabling technologies. The test bed radar includes a direct digital synthesizer (DDS) for frequency-diverse waveform generation, a flexible wideband transceiver for bandwidth extension and frequency translation, and an open architecture signal processor with embedded wideband analog-to-digital converters for real-time acquisition and processing. Efficient signal processing algorithms have been developed to demonstrate multimode radar capability. This paper discusses the various subassemblies, algorithm efficiency, and field experiment results     

Moving target detection via airborne HRR phased array radar

We study moving target detection in the presence of temporally and spatially correlated ground clutter for airborne high range resolution (HRR) phased array radar. We divide the HRR range profiles into large range segments to avoid the range migration problems that occur in the HRR radar data. Since each range 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 autoregressive (VAR) filtering technique to suppress the ground clutter. Then a moving target detector based on a generalized likelihood ratio test (GLRT) detection strategy is derived. The detection threshold is determined according to the desired false alarm rate, which is made possible via an asymptotic statistical analysis. After the target Doppler frequency and spatial signature vectors are estimated from the VAR-filtered data as if a target were present, a simple detection variable is computed and compared with the detection threshold to render a decision on the presence of a target. Numerical results are provided to demonstrate the performance of the proposed moving target detection algorithm     

GLRT Detectors for Aircraft Wake Vortices in Clear Air

 In this article, radar echoes of aircraft wake vortices are modeled as weighted sums of the frequency components of the echoes with a special covariance matrix for the weighted coefficients. With a proposed detection scheme, two generalized likelihood ratio test (GLRT) detectors are derived respectively for aircraft wake vortices with time-varying and time-invariant Doppler spectra. Then the analytical expressions for detection and false alarm probabilities of the detectors are derived and three factors are investigated which mainly influence the detection performance, i.e., the Doppler extension and uncertainty of the aircraft wake vortex, and the number of the detection cells. The results indicate that, the signal-to-noise ratio (SNR) loss induced by Doppler extension is generally several decibels. The SNR loss due to Doppler uncertainty is approximately proportional to the logarithm of the number of spectrum lines in the uncertain Doppler spectrum intervals. For a large number of detection cells, the SNR gain is approximately proportional to the square root of the number of the detection cells.     

应用反推神经网络检测液体火箭发动机多维故障

基于可测参数所构成的参数模式对应着一定的发动机故障模式, 应用反推神经网络检测发动机多维故障, 方法的有效性由只有泵效率下降和喷注器阻塞同时发生的数值仿真得到验证      

A CFAR adaptive matched filter detector

An adaptive algorithm for radar target detection using an antenna array is proposed. The detector is derived in a manner similar to that of the generalized likelihood-ratio test (GLRT) but contains a simplified test statistic that is a limiting case of the GLRT detector. This simplified detector is analyzed for performance to signals on boresight, as well as when the signal direction is misaligned with the look direction     

基于改进A-Star算法的隐身无人机快速突防航路规划

针对现代战争中隐身无人机（UAV）在高严密的组网雷达防御体系下的生存及突防问题,提出了基于改进A-Star算法的隐身无人机战区突防航路规划技术。首先对隐身无人机突防过程进行了分析建模,分别建立了隐身无人机的运动学模型、动态雷达散射截面特性和组网雷达探测概率的计算模型。然后针对传统算法在解决隐身突防问题时的不足,充分考虑所规划航路时的快速性和安全性要求,设计了改进A-Star算法。在算法中引入了多层变步长搜索策略和无人机的姿态角信息,结合秩K融合准则,通过每段航迹上隐身无人机被组网雷达系统的发现概率来判断新航迹点的可行性。仿真结果表明,改进A-Star算法能够在复杂的组网雷达系统下快速生成更优的战区突防航路,具有一定的应用价值。     

Multi-Target/Multi-Sensor Tracking using Only Range and Doppler Measurements

A new approach is described for combining range and Doppler data from multiple radar platforms to perform multi-target detection and tracking. In particular, azimuthal measurements are assumed to be either coarse or unavailable, so that multiple sensors are required to triangulate target tracks using range and Doppler measurements only. Increasing the number of sensors can cause data association by conventional means to become impractical due to combinatorial complexity, i.e., an exponential increase in the number of mappings between signatures and target models. When the azimuthal resolution is coarse, this problem will be exacerbated by the resulting overlap between signatures from multiple targets and clutter. In the new approach, the data association is performed probabilistically, using a variation of expectation-maximization (EM). Combinatorial complexity is avoided by performing an efficient optimization in the space of all target tracks and mappings between tracks and data. The full, multi-sensor, version of the algorithm is tested on simulated data. The results demonstrate that accurate tracks can be estimated by exploiting spatial diversity in the sensor locations. Also, as a proof-of-concept, a simplified, single-sensor range-only version of the algorithm is tested on experimental radar data acquired with a stretch radar receiver. These results are promising, and demonstrate robustness in the presence of nonhomogeneous clutter.     

Doppler Compensation & Single Pulse Imaging using Adaptive Pulse Compression

The effects of target Doppler are addressed in relation to adaptive receive processing for radar pulse compression. To correct for Doppler-induced filter mismatch over a single pulse, the Doppler-compensated adaptive pulse compression (DC-APC) algorithm is presented whereby the respective Doppler shifts for large target returns are jointly estimated with the illuminated range profile and subsequently incorporated into the original APC adaptive receive filter formulation. As a result, the Doppler-mismatch-induced range sidelobes can be suppressed thereby regaining a significant portion of the sensitivity improvement that is possible when applying adaptive pulse compression (APC) without the existence of significant Doppler mismatch. In contrast, instead of compensating for Doppler mismatch, the single pulse imaging (SPI) algorithm generalizes the APC formulation for a bank of Doppler-shifted matched filters thereby producing a sidelobe-suppressed range-Doppler image from the return signal of a single radar pulse which is applicable for targets with substantial variation in Doppler. Both techniques are based on the recently proposed APC algorithm and its generalization, the multistatic adaptive pulse compression (MAPC) algorithm, which have been shown to be effective for the suppression of pulse compression range sidelobes thus dramatically increasing the sensitivity of pulse compression radar.     

Systematic Approach for Classification of Modern Surveillance Radar Systems

Inherent search volume is proposed as a tool for systematic comparison of modern phased-array surveillance radar systems. The advantage of the inherent search volume over the existing approaches based on single-scan and cumulative probability of detection is that the inherent search volume depends only on the unadjustable parameters of the radar. A comparison algorithm based on the inherent search volume criterion is presented.     

A novel range-Doppler imaging algorithm with OFDM radar

Traditional pulse Doppler radar estimates the Doppler frequency by taking advantage of Doppler modulation over different pulses and usually it requires a few pulses to estimate the Doppler frequency. In this paper, a novel range-Doppler imaging algorithm based on single pulse with orthogonal frequency division multiplexing(OFDM) radar is proposed, where the OFDM pulse is composed of phase coded symbols. The Doppler frequency is estimated using one single pulse by utilizing Doppler modulation over different symbols, which remarkably increases the data update rate. Besides, it is shown that the range and Doppler estimations are completely independent and the well-known range-Doppler coupling effect does not exist. The effects of target movement on the performances of the proposed algorithm are also discussed and the results show that the algorithm is not sensitive to velocity. Performances of the proposed algorithm as well as comparisons with other range-Doppler algorithms are demonstrated via simulation experiments.