基于平面图形的典型浮标规划算法

针对海上应召反潜、检查反潜等常规任务场景以及新型浮标的使用,本文提出了基于折线阵、多直线阵和方形覆盖阵共三种平面图形的典型浮标规划算法,通过优化设置参数和改进规划阵形生成不同的浮标布阵方案。仿真表明该三种图形种类丰富,广泛适用于目标搜索阶段,满足应召反潜、检查反潜等常规反潜任务场景的使用需求,相比于传统规划阵形,具有更高的目标搜索概率。     

基于自适应线谱增强的LOFAR浮标信号处理及Doppler-CPA定位方法

LOFAR浮标是一种被动全向浮标,用于对潜搜索的初始阶段。常规的LOFAR谱图对于小信噪比和有色背景噪声处理性能下降。文中采用自适应线谱增强技术将目标辐射中的线谱成分从背景噪声中分离出来进行LOFAR谱图分析,提高LOFAR浮标的检测性能。在LOFAR分析的基础上利用目标的多普勒信息,采用Doppler-CAP方法测算目标的速度和目标与浮标的距离,初步估算出目标的航迹。仿真结果表明,新的LOFAR浮标数据处理算法检测性能更好,能够得到目标与浮标最接近点的距离。     

基于非线性运算的水下弱目标回波积累检测算法研究

为了有效地检测出淹没在背景噪声中的水下弱目标回波信号,建立高斯噪声和脉冲噪声背景下的水下弱目标多脉冲回波模型,并导出匹配滤波器的输出模型,提出基于非线性运算的目标回波积累检测算法,利用该算法检测淹没在背景噪声下的弱目标回波信号。结果表明,无论是高斯噪声还是脉冲噪声、静止目标还是匀速运动目标,该算法均能有效地检测出目标回波信号。     

基于多层感知机的远距离水下声源定位技术研究

针对传统匹配场处理方法存在水下声源远距离定位失准以及定位时间过长的问题，提出了一种基于多层感知机的水下声源被动定位方案。利用团队自研的“浮星”浮标实测的剖面数据模拟真实海洋环境，并在水中布设垂直水听器阵，仿真大量不同位置的声源在水听器处产生的接收数据。将多通道波形数据直接作为输入对多层感知机网络进行训练，从而获取高精度的定位神经网络。仿真结果表明，与匹配场处理算法相比，设计的感知机网络可以在大范围信噪比环境中实现有效的水下声源定位，其中在30dB信噪比下定位距离和深度的平均相对误差达到了1.94%和6.84%。另外，相对于失配声速剖面，使用平均声速剖面模拟的接收数据可提高网络的定位性能。     

反潜鱼雷靶试水下被动跟踪定位精度

跟踪重构鱼雷水下运动轨迹，对准确评估鱼雷状况及性能至关重要。文章研究了靶试环境下通过被动声纳浮标阵列跟踪某反潜鱼雷的定位精度。根据靶试对被动声纳浮标阵列要求，采用改进的代数方程方法定位鱼雷目标，通过蒙特卡洛仿真，研究对水下鱼雷的跟踪定位精度，为开展鱼雷靶试工作提供指导。     

声纳浮标阵目标搜索优化布放算法

为提高声纳浮标阵的目标搜索效率,文章首先建立目标运动模型和累积搜索概率的计算方法,然后提出了基于多点随机搜索、分区分支界定和遗传算法的浮标阵优化布放方法。仿真结果表明：这3种优化方法均优于传统布放方法,多点随机搜索算法性能最差但适合短时间制定布放策略;分区分支界定算法适合优化较少参数的浮标阵形,保证能找到最优点;对于较...     

航空反潜任务中的浮标定位阵参数计算方法

介绍了航空反潜作战中在单枚浮标与目标发生声接触的条件下计算后续浮标定位阵的布放参数的方法。根据航空检查反潜或应召反潜的作战任务及初始已知的目标参数,结合载机飞行特性,给出未来时刻目标的态势散布结果,进而依据态势散布情况和浮标特性给出后续布放浮标定位阵的阵形参数,及其搜索定位概率指标,对智能化浮标定位辅助决策具有较强的指导意义。     

线形浮标阵搜潜时无人机监听航路规划

航空反潜时,无人机代替有人机对浮标阵进行监听是无人机在未来战场上的重要应用之一。以无人机独立执行监听线形浮标阵任务为背景,在对巡逻搜潜时线形浮标阵的布设进行分析并提出无人机航路的代价函数后,根据浮标阵的特点,规划出了平行监听和垂直监听2种无人机监听浮标阵方案,并对所规划航路的技术指标进行了分析。通过仿真,对这2种方案进行了验证,仿真结果分析表明了2种方案的优劣。     

基于检测前跟踪的超视距雷达微弱目标检测方法

天波超视距雷达（over-the-horizonradar,OTHR）通过快速傅立叶变换（FFr）实现相干积累,再利用常规的方法进行目标检测。但这种方法在弱目标、低信噪比的情况下效果并不好。本文提出了一种基于检测前跟踪（track-before-detect,TBD）的OTHR弱目标检测方法,利用数学形态学对每帧弱目标回波信号进行滤波,再通过动态规划方法进行检测。仿真结果表明,该方法能够有效地提高OTHR对弱目标的检测能力,运算效率高,实用性强。     

用GPS确定漂泊的浮标位置

弹道导弹的试验要求精确确定再入体的溅落点。一般利用声纳浮标导弹落点定位系统(SMILS)来测定。在靶标阵中投入15个浮标,每个浮标可检测再入体溅落产生的声(在水中)响,并把溅落数据发射到空中盘旋的飞机上去。这里最重要的是知道每个浮标的地理位置。下面叙述根据来自GPS的信号确定浮标位置的方法。     

主/被动联合多基地航空搜潜范围分析

 在主/被动联合多基地航空搜潜条件下,根据声纳、浮标、潜艇的位置关系,推导出了对目标定位的数学模型,并结合主/被动声纳方程,建立了目标与主动声纳和浮标之间的位置关系、主动声纳的最大传输距离、多基地搜潜的搜潜范围和定位范围等数学模型,在此基础上,分析了搜潜范围与主动声纳和浮标距离之间的关系、目标与主动声纳和目标与浮标距离之间的关系、浮标位置与搜潜范围和定位范围之间的关系等,获得了有益的结果。     

Data association for deghosting in Y-shaped passive linear array sonars

This paper deals with data association using three sets of passive linear array sonars (PLAS) geometrically positioned in a Y-shaped configuration, fixed in an underwater environment. The data association problem is directly transformed into a 3D assignment, which is known to be NP hard. For generic passive sensors, it can be solved using conventional algorithms, while in PLAS, it becomes a formidable task due to the presence of bearing ambiguity. Thus, the central issue of the problem in PLAS is how to eliminate the bearing ambiguity without increasing tracking error. To solve this problem, the 3D assignment algorithm used the likelihood value of only those observed bearing measurements is modified by incorporating frequency information in consecutive time-aligned scans. The region of possible ghost targets is first established by the geometrical relation of PLAS with respect to target. The ghost targets are then confirmed and eliminated by generating multiple observations in consecutive scans. Representative simulations demonstrate the effectiveness of the proposed approach.     

A Multistage Processing Algorithm for Disturbance Removal and Target Detection in Passive Bistatic Radar

The paper examines the problem of cancellation of direct signal, multipath and clutter echoes in passive bistatic radar (PBR). This problem is exacerbated as the transmitted waveform is not under control of the radar designer and the sidelobes of the ambiguity function can mask targets including those displaced in either (or both) range and Doppler from the disturbance. A novel multistage approach is developed for disturbance cancellation and target detection based on projections of the received signal in a subspace orthogonal to both the disturbance and previously detected targets. The resulting algorithm is shown to be effective against typical simulated scenarios with a limited number of stages, and a version with computational savings is also introduced. Finally its effectiveness is demonstrated with the application to real data acquired with an experimental VHF PBR system.     

EM-ML algorithm for track initialization using possibly noninformative data

Initializing and maintaining a track for a low observable (LO) (low SNR, low target detection probability and high false alarm rate) target can be very challenging because of the low information content of measurements. In addition, in some scenarios, target-originated measurements might not be present in many consecutive scans because of mispointing, target maneuvers, or erroneous preprocessing. That is, one might have a set of noninformative scans that could result in poor track initialization and maintenance. In this paper an algorithm based on the expectation-maximization (EM) algorithm combined with maximum likelihood (ML) estimation is presented for tracking slowly maneuvering targets in heavy clutter and possibly noninformative scans. The adaptive sliding-window EM-ML approach, which operates in batch mode, tries to reject or weight down noninformative scans using the Q-function in the M-step of the EM algorithm. It is shown that target features in the form of, for example, amplitude information (AI), can also be used to improve the estimates. In addition, performance bounds based on the supplemented EM (SEM) technique are also presented. The effectiveness of new algorithm is first demonstrated on a 78-frame long wave infrared (LWIR) data sequence consisting of an Fl Mirage fighter jet in heavy clutter. Previously, this scenario has been used as a benchmark for evaluating the performance of other track initialization algorithms. The new EM-ML estimator confirms the track by frame 20 while the ML-PDA (maximum likelihood estimator combined with probabilistic data association) algorithm, the IMM-MHT (interacting multiple model estimator combined with multiple hypothesis tracking) and the EVIM-PDA estimator previously required 28, 38, and 39 frames, respectively. The benefits of the new algorithm in terms of accuracy, early detection, and computational load are illustrated using simulated scenarios as well.     

Array shape estimation tracking using active sonar reverberation

This paper concerns the problem of array shape estimation and tracking for towed active sonar arrays, using received reverberation returns from a single transmitted CW pulse. Uniform linear arrays (ULAs) deviate from their nominal geometry while being towed due to ship maneuvers as well as ocean currents. In such scenarios, conventional beamforming performed under the assumption of a ULA can sometimes lead to unacceptably high spatial sidelobes. The reverberation leaking through the sidelobes can potentially mask weak targets in Doppler, especially when the target Doppler is close to that of the mainlobe reverberation and the reverberation-to-target ratio (RTR) is very high. Although heading sensors located along the array can be used to provide shape estimates, they may not be sufficiently available or accurate to provide the required sidelobe levels. We propose an array shape calibration algorithm using multipath reverberation returns from each ping as a distributed source of opportunity. More specifically, a maximum likelihood (ML) array shape calibration algorithm is developed, which exploits a deterministic relationship between the reverberation spatial and Doppler frequencies causing it to be low rank in the space-time vector space formed across a single coherent processing interval (CPI). In this application, a sequence of overlapped CPI length snapshots of duration less than the CW pulse is used. The ML estimates obtained for each snapshot are tracked using a Kalman filter with a state equation corresponding to the water pulley model for array dynamics. Simulations performed using real heading sensor data in conjunction with simulated reverberation suggest that 8-10 dB improvement in sidelobe level may be possible using the proposed array shape tracking algorithm versus an algorithm that uses only the available heading information.     

运动单阵元被动合成阵列波达方向估计

 提出了一种运动单阵元被动合成阵列波达方向(DOA)估计算法。该算法基于被动合成阵列(PSA)的概念,结合空间谱估计的思想构建了运动单阵元被动合成阵列模型,通过多次不同速度合成阵列过程实现对信号DOA的无模糊估计。通过对单次匀速合成阵列过程进行分析得到,在假设信号频率已知条件下,合成阵列算法能够达到与同孔径实阵列多重信号分类（MUSIC）算法相当的DOA估计性能。仿真验证了被动合成阵列与同孔径实阵列的渐近等效性及算法的有效性。     

Directed Subspace Search ML-PDA with Application to Active Sonar Tracking

The maximum likelihood probabilistic data association (ML-PDA) tracking algorithm is effective in tracking Very Low Observable targets (i.e., very low signal-to-noise ratio (SNR) targets in a high false alarm environment). However, the computational complexity associated with obtaining the track estimate in many cases has precluded its use in real-time scenarios. Previous ML-PDA implementations used a multi-pass grid (MPG) search to find the track estimate. Two alternate methods for finding the track estimate are presented-a genetic search and a newly developed directed subspace (DSS) search algorithm. Each algorithm is tested using active sonar scenarios in which an autonomous underwater vehicle searches for and tracks a target. Within each scenario, the problem parameters are varied to illustrate the relative performance of each search technique. Both the DSS search and the genetic algorithm are shown to be an order of magnitude more computationally efficient than the MPG search, making possible real-time implementation. In addition, the DSS search is shown to be the most effective technique at tracking a target at the lowest SNR levels-reliable tracking down to 5 dB (postprocessing SNR in a resolution cell) using a 5-frame sliding window is demonstrated, this being 6 dB better than the MPG search.     

典型水文环境下航空声呐浮标双基地作用范围

航空声呐浮标双基地探测是应对水下目标声隐身能力持续提高的有效技术途径之一。分析了航空声呐浮标的指标,给出了双基地声呐配置,采用双基地声呐方程为依据,利用数值仿真的方法计算了 3种典型海洋环境条件下双基地声呐浮标探测范围,讨论了海洋环境对双基地声呐探测的影响,为航空声呐浮标双基地战术使用奠定技术基础。