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Comparison of Real-time Implementation of Conventional and Adaptive Triplet Array Beamforming Algorithms for Pulsed Active Sources

机译:常规和自适应三重态阵列波束形成算法在脉冲有源源上实时实现的比较

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A triplet array has the capability to reduce the port/starboard ambiguity that strongly affects detection and localization in the case of a linear array. When searching for a target near a high clutter area (e.g., a rocky shore near a cliff), this feature can be crucial for detection. The most computationally intensive part of the detection and localization process is the beamforming. This work describes three beamforming algorithms that have been implemented at NATO STO-CMRE for real-time signal processing on board an Autonomous Underwater Veicle (AUV) towing a triplet array: a conventional cardioid beamformer, a 3D cardioid beamformer and an adaptive beaformer. The three algorithms are compared in terms of run-time and memory usage, parameters that are particularly important as the array is intended to be used on an AUV with limited computational power. Other criteria for comparison evaluated in this work are the spatial resolution and the Port/Starboard Rejection. The algorithms are evaluated against a data set collected during the LCAS16 sea trial (off the coast of Taranto, Italy) and the LCAS18 sea trial (off the northern cost of Elba). The results, in term of accuracy, spatial resolution, Port/Starboard Amplitude Rejection (PSAR), computation time and memory usage, are given for the three algorithms.
机译:三重态阵列具有减少在线性阵列情况下严重影响检测和定位的左舷/右舷模糊性的能力。在高杂波区域附近(例如悬崖附近的多岩石的海岸)搜索目标时,此功能对于检测至关重要。检测和定位过程中计算量最大的部分是波束成形。这项工作描述了三种由北约STO-CMRE实施的波束成形算法,用于在拖曳三重态阵列的自主水下航行器(AUV)上进行实时信号处理:传统的心形波束形成器,3D心形波束形成器和自适应波束形成器。比较了三种算法的运行时间和内存使用情况,这些参数特别重要,因为该阵列打算以有限的计算能力在AUV上使用。在这项工作中评估的其他比较标准是空间分辨率和左舷/右舷拒绝。根据在LCAS16海上试验(意大利塔兰托沿海)和LCAS18海上试验(在厄尔巴岛北部成本以外)收集的数据集对算法进行了评估。给出了三种算法的准确性,空间分辨率,左舷/右舷幅度抑制(PSAR),计算时间和内存使用情况的结果。

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