UWB signal acquisition in positioning systems: Bayesian compressed sensing with redundancy (original) (raw)

Compressive sensing based sub-mm accuracy UWB positioning systems: A space–time approach

Digital Signal Processing, 2013

A key challenge to achieve very high positioning accuracy (such as sub-mm accuracy) in Ultra-Wideband (UWB) positioning systems is how to obtain ultra-high resolution UWB echo pulses, which requires ADCs with a prohibitively high sampling rate. The theory of Compressed Sensing (CS) has been applied to UWB systems to acquire UWB pulses below the Nyquist sampling rate. This paper proposes a front-end optimized scheme for the CS-based UWB positioning system. A Space-Time Bayesian Compressed Sensing (STBCS) algorithm is developed for joint signal reconstruction by transferring mutual a priori information, which can dramatically decrease ADC sampling rate and improve noise tolerance. Moreover, the STBCS and time difference of arrival (TDOA) algorithms are integrated in a pipelined mode for fast tracking of the target through an incremental optimization method. Simulation results show the proposed STBCS algorithm can significantly reduce the number of measurements and has better noise tolerance than the traditional BCS, OMP, and multi-task BCS (MBCS) algorithms. The sub-mm accurate CS-based UWB positioning system using the proposed STBCS-TDOA algorithm requires only 15% of the original sampling rate compared with the UWB positioning system using a sequential sampling method.

Compressed sensing based UWB receiver: Hardware compressing and FPGA reconstruction

2009 43rd Annual Conference on Information Sciences and Systems, 2009

A low sampling rate approach for recovering ultra wide band (UWB) signals is proposed, using Distributed Amplifiers (DAs) and low speed Analog-to-Digital Converters (ADCs) and based on the theory of compressed sensing. A microwave circuit consisting of a bank of DAs, followed by a bank of ADCs, is designed to implement analog compressing, where the elements of measurement matrix are realized by picosecond delay tap and flexible gain coefficients in DAs. Numerical simulation shows that a bank of eight DAs and ADCs with 500MHz sampling rate can almost perfectly recover a 100ps-resolution UWB echo signal in the noiseless case. For recovering the UWB signals in a real-time way, issues in field programmable gate array (FPGA) implementation are discussed.

Ultra-Wideband Compressed Sensing: Channel Estimation

IEEE Journal of Selected Topics in Signal Processing, 2007

In this paper, ultra-wideband (UWB) channel estimation based on the theory of compressive sensing (CS) is developed. The proposed approach relies on the fact that transmitting an ultra-short pulse through a multipath UWB channel leads to a received UWB signal that can be approximated by a linear combination of a few atoms from a pre-defined dictionary, yielding thus a sparse representation of the received UWB signal. The key in the proposed approach is in the design of a dictionary of parameterized waveforms (atoms) that closely matches the information-carrying pulseshape leading thus to higher energy compaction and sparse representation, and, therefore higher probability for CS reconstruction. Two approaches for UWB channel estimation are developed under a data-aided framework. In the first approach, the CS reconstruction capabilities are exploited to recover the composite pulse-multipath channel from a reduced set of random projections. This reconstructed signal is subsequently used as a referent template in a correlator-based detector. In the second approach, from a set of random projections of the received pilot signal, the Matching Pursuit algorithm is used to identify the strongest atoms in the projected signal that, in turn, are related to the strongest propagation paths that composite the multipath UWB channel. A Rake like receiver uses those atoms as templates for the bank of correlators in the detection stage. The bit error rate performances of the proposed approaches are analyzed and compared to that of traditional correlator-based detector. Extensive simulations show that for different propagation scenarios and UWB communication channels, detectors based on CS channel estimation outperform traditional correlator using just 1/3 of the sampling rate leading thus to a reduced use of analog-to-digital resources in the channel estimation stage.

Compressed Sensing for OFDM UWB Systems

Radio and Wireless …

This paper considers compressed sensing (CS) techniques for signal reconstruction and channel estimation in OFDM-based high-rate ultra wideband (UWB) communication systems. We employ a parallel CS structure that exploits frequency domain sparsity. We also consider multipath UWB channels in both the line-of-sight and non line-of-sight environments. UWB signal detection and channel estimation from sub-Nyquist analog projections is carried out using an optimized orthogonal matching pursuit algorithm and the smoothed ℓ0 algorithm. Simulation results demonstrate significant gains in the form of reliable signal recovery and channel estimation as well as dramatically sub-Nyquist sampling rates for the analog-to-digital converters while maintaining high data rates.

Compressed Sensing for Ultrawideband Impulse Radio

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007

In this paper, ultrawideband (UWB) channel estimation based on the novel theory of Compressive Sensing (CS) is developed. The proposed approach relies on the fact that transmitting an ultra-short UWB pulse through a multipath channel leads to a received UWB signal that can be approximated by a linear combination of a few atoms from a pre-de ned dictionary, yielding thus a sparse representation of the received signal. The CS reconstruction capabilities are exploited to recover the composite pulse-multipath channel from a reduced set of random projections using the Matching Pursuit algorithm. This reconstructed signal is subsequently used as a referent template in a correlator based detector. Extensive simulations show that for different propagation scenarios and UWB communication environments, the CS detector outperforms traditional correlators using just 1/3 of the sampling rate leading thus to a reduced use of analog-to-digital resources in the channel estimation stage.

Compressed UWB signal detection with narrowband interference mitigation

IEEE International Conference on Ultra-Wideband, 2008

Operating at sub-Nyquist rate, compressed sensing (CS) has been successfully applied to the design of impulse ultra-wideband (I-UWB) receivers where Nyquist sampling is a formidable challenge. However, strong narrowband interference (NBI) can easily jam and saturate the receiver front-end and greatly degrade the system performance. In this paper, CS is applied to the design of I-UWB receivers with NBI mitigation. By exploiting the sparsity of the NBI within the pulse UWB spectrum, a compressive measurement matrix can be designed that is not only efficient at collecting signal energy, but also nulls out the NBI effectively. The performance analysis of the proposed receiver is provided. Simulation results show the effectiveness of the proposed method for UWB signal detection and NBI mitigation.

Compressed detection for ultra-wideband impulse radio

IEEE Workshop on Signal Processing Advances in Wireless Communications, 2007

The emerging theory of compressed sensing (CS) not only enables the reconstruction of sparse signals from a small set of random measurements [1, 2], but also provides an universal signal detection approach at sub-Nyquist sampling rates [3, 4]. Compressed signal detection is particularly suitable for impulse ultra-wideband (I-UWB) communications where Nyquist sampling of the signal is a formidable challenge [5]. In this paper, we propose a generalized likelihood ratio test (GLRT) detector for I-UWB receivers based on compressive measurements. Pilot symbol assisted modulation is proposed where received signals are randomly projected and subsequently correlated for data demodulation. The proposed receiver is simple to implement, which has the advantage that neither wideband delay lines nor ultra-fast analog to digital converters (ADC) are required. Given a channel realization, the exact bit error probability (BEP) of the proposed receiver is derived. Approximate BEP is also derived under the Gaussian assumption. Simulation results show that the proposed receiver with moderate compressive measurements has comparable performance to traditional analog autocorrelation (AcR) receivers [6,7].