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This paper presents a distributed optimization method for informative trajectory planning in multi-target tracking problems. The purpose of such problems is to optimize a sequence of waypoints/control inputs of mobile sensors over a certain future time step to minimize the uncertainty of targets. The planning problem is reformulated as a distributed optimization problem that can be expressed in the form of a subproblem for each target. The subproblems are coupled using the distributed Alternating Direction Method of Multipliers (ADMM). This coupling not only enables the results of each subproblem to be reflected in the optimization process of the other subproblems, but also guides the results of the subproblems to converge to the same solution. In contrast to existing approaches performing trajectory optimization after assigning tasks, the proposed algorithm does not require the design of a heuristic cost function for task assignment, and it can handle both non-myopic trajectory planning and task assignment in multiple target tracking problems simultaneously. In order to reduce the computation time of the algorithm, an edge-cutting method suitable for multiple target tracking problems is proposed, as a receding-horizon control scheme for real-time implementation, which considers the computation time. Numerical examples are presented to demonstrate the applicability of the algorithm.

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A compact CMOS magnetic Hall sensor that includes both a Hall plate and readout circuit is proposed. In order to achieve a low-noise and low-power operation, the sensor employs a switched biasing amplifier with a chopper. The prototype has been implemented and fabricated in a high-voltage 0.18 m CMOS process and occupies 0.624 mm 2 . Owing to the switched biasing amplifier, the input-referred noise is reduced from 41 T Hz to 25 T Hz. The entire sensor consumes mW with a 3.3 V supply voltage.Index Terms-1 f noise, CMOS, dynamic offset cancellation, magnetic Hall sensor, switched biasing amplifier.

A wavelet Electrocardiogram (ECG) detector for low-power implantable cardiac pacemakers is presented in this paper. The proposed wavelet-based ECG detector consists of a wavelet decomposer with wavelet filter banks, a QRS complex detector of hypothesis testing with wavelet-demodulated ECG signals, and a noise detector with zero-crossing points. In order to achieve high detection accuracy with low power consumption, a multi-scaled product algorithm and soft-threshold algorithm are efficiently exploited in our ECG detector implementation. Our algorithmic and architectural level approaches have been implemented and fabricated in a standard 0.35 μm CMOS technology. The testchip including a low-power analog-to-digital converter (ADC) shows a low detection error-rate of 0.196% and low power consumption of 19.02 μW with a 3 V supply voltage.

This paper presents a double‐sharpened decimation filter based on the application of a Kaiser and Hamming sharpening technique for multistandard wireless systems. The proposed double‐sharpened decimation filter uses a pre‐droop compensator which improves the passband response of a conventional cascaded integrator‐comb filter so that it provides an efficient sharpening performance at half‐speed with comparison to conventional sharpened filters. In this paper, the passband droop characteristics with compensation provides –1.6 dB for 1.25 MHz, –1.4 dB for 2.5 MHz, –1.3 dB for 5 MHz, and –1.0 dB for 10 MHz bandwidths, respectively. These results demonstrate that the proposed double‐sharpened decimation filter is suitable for multistandard wireless applications.