标题： 基于盲斜投影结合噪声白化的闭式连续相对传输函数向量估计 显示英文标题

标题： Closed-Form Successive Relative Transfer Function Vector Estimation based on Blind Oblique Projection Incorporating Noise Whitening

摘要： 相对传递函数(RTFs)在波束成形中起着关键作用，能够有效抑制噪声和干扰。 本文解决了在嘈杂和混响环境中在线估计多个声源的RTF向量的挑战，特别是在声源依次激活的特定场景下。 虽然第一个声源的RTF向量可以直接估计，但在多个声源同时激活的段落中估计后续声源的RTF向量是主要挑战。 盲斜投影(BOP)方法被提出用于通过最优阻塞新激活声源来估计其RTF向量。 然而，该方法面临几个限制：由于依赖于迭代梯度下降优化而导致的高计算复杂度，引入的随机附加向量可能对性能产生负面影响，以及假设信号噪声比(SNR)较高。 为克服这些限制，本文提出了BOP方法的三个扩展。 首先，我们推导了优化BOP代价函数的闭式解，显著降低了计算复杂度。 其次，我们引入正交附加向量而不是随机向量，提高了RTF向量估计的准确性。 第三，我们引入了受协方差减法和白化启发的噪声处理技术，在低SNR条件下提高了鲁棒性。 为了提供逐帧的源活动模式估计，这对传统BOP方法和所提方法都是必需的，我们提出了一种基于空间相干性的在线源计数方法。 使用包含3个依次激活说话人的实际混响噪声录音进行了仿真，有无先验的源活动模式知识。 显示英文摘要

摘要： Relative transfer functions (RTFs) of sound sources play a crucial role in beamforming, enabling effective noise and interference suppression. This paper addresses the challenge of online estimating the RTF vectors of multiple sound sources in noisy and reverberant environments, for the specific scenario where sources activate successively. While the RTF vector of the first source can be estimated straightforwardly, the main challenge arises in estimating the RTF vectors of subsequent sources during segments where multiple sources are simultaneously active. The blind oblique projection (BOP) method has been proposed to estimate the RTF vector of a newly activating source by optimally blocking this source. However, this method faces several limitations: high computational complexity due to its reliance on iterative gradient descent optimization, the introduction of random additional vectors, which can negatively impact performance, and the assumption of high signal-to-noise ratio (SNR). To overcome these limitations, in this paper we propose three extensions to the BOP method. First, we derive a closed-form solution for optimizing the BOP cost function, significantly reducing computational complexity. Second, we introduce orthogonal additional vectors instead of random vectors, enhancing RTF vector estimation accuracy. Third, we incorporate noise handling techniques inspired by covariance subtraction and whitening, increasing robustness in low SNR conditions. To provide a frame-by-frame estimate of the source activity pattern, required by both the conventional BOP method and the proposed method, we propose a spatial-coherence-based online source counting method. Simulations are performed with real-world reverberant noisy recordings featuring 3 successively activating speakers, with and without a-priori knowledge of the source activity pattern.