在這篇論文中，我們提出基於感測器分群 (sensor clustering)之合作式訊息聚集 (cooperative information aggregation) 方法來改善估測效能。首先，我們將感測器分成多個群組，透過門檻分配 (threshold allocation) 的設計方法，使得多個群組共同合作估測單一未知訊號源，使感測區間 (sensing window) 內的解析度提升。在資訊融合中心 (fusion Center) ，我們提出兩種檢測估計方法，硬決策估計子 (hard decision estimator) 以及軟決策估計子 (soft decision estimator)，加以利用全部群組中的資訊。另外，為了更進一步提升估測效能，我們提出可適性感測區間 (adaptive sensing window) 演算法。利用回饋機制 (feedback mechanism) 將感測區間做適應性地調整以提高解析度。結果顯示，基於感測器分群之合作式訊息聚集方法相較於傳統的合作式訊息聚集方法更能夠提供較佳的標準均方誤差 (NMSE) 在二進位對稱通道 (binary symmetric channels)中較低的交叉機率 (crossover probability) 區間。此外，隨著觀測雜訊 (observation noise) 的上升，基於感測器分群之合作式訊息聚集方法相較於合作式訊息聚集方法有較佳的抗雜訊能力。

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