• 전기학회논문지
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• 제61권2호
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1788-1789
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• 2011

In order to develop a one-axis gimbaled acoustic source tracker for mobile robots, a pseudo-linear direction of arrival(DOA) estimator is proposed using a linear ultrasonic sensor array. Under the assumption that the sensor measurement errors are negligible, a linear measurement model is derived using the linear prediction relation of the received sinusoidal acoustic signals. Applying the Kalman filtering technique for this model, the linear recursive DOA estimator is designed. For its linear recursive filter structure, it is preferable for real-time implementation on a commercial DSP. Through the experiments, the effectiveness of the suggested method is demonstrated.