Yingyi Tan

Cramer-Rao lower bound for estimating quadrupole resonance signals in non-Gaussian noise

Quadrupole resonance (QR) technology for the detection of explosives is of crucial importance in an increasing number of applications. For landmine detection, where the detection system cannot be shielded, QR has proven to be highly effective if the QR sensor is not exposed to radio-frequency interference (RFI). However, strong non-Gaussian RFI in the field is unavoidable. A statistical model of such non-Gaussian RFI noise is given in this letter. In addition, the asymptotic Cramer-Rao lower bound for estimating a deterministic QR signal in this non-Gaussian noise is presented. The performance of several convenient estimators is compared to this bound.

Landmine detection with nuclear quadrupole resonance

Nuclear quadrupole resonance (NQR) technology for the detection of explosives is of crucial importance in an increasing number of applications. For landmine detection, NQR has proven to be highly effective if the NQR sensor is not exposed to radio frequency interference (RFI). Since strong nonstationary RFI in the field is unavoidable, a robust detection method is required. With the aid of reference antennas, a frequency domain LMS algorithm is applied to cancel the RFI in field data. An average power detector based on power spectral estimation algorithms is proposed and performance using both the periodogram and MUSIC algorithms is evaluated. The detection performance has been compared with that of a non-adaptive Bayesian detector. The experimental results show that, unlike the non-adaptive Bayesian detector, the average power detector provides perfect detection capability if the data segments involved in the collection process are sufficiently long.

Kalman filtering for enhanced landmine detection using quadrupole resonance

Quadrupole resonance (QR) is a novel technology recently applied to landmine detection. The detection process is specific to the chemistry of the explosive, and therefore is less susceptible to the types of false alarms experienced by metal detectors and ground-penetrating radars. Although QR is vulnerable to radio-frequency interference (RFI) when the sensor is deployed in the field, adaptive RFI mitigation can remove most of the RFI. In this paper, advanced signal processing algorithms applied to the postmitigation signal are studied to enhance explosive detection. A new Kalman filtering strategy is proposed to estimate and detect the QR signal in the postmitigation signal. The results using both simulated data and experimental data show that the proposed algorithm can provide robust landmine detection performance.

Enhanced Auditory Displays for Discriminating Landmines from Clutter Using Electromagnetic Induction Sensors

Landmine detection is primarily performed using electromagnetic induction (EMI) sensors. These sensors detect the presence of metal and convey the information to the sensor operators via an audio signal. Reduction of false alarms from objects that contain metal but are not landmines, i.e. discrimination, is a challenging problem. Recent work on automated algorithms has shown promise towards reducing false alarm rates of EMI sensors. In this study, the audio signal was modified to encode the presence of metal as well as information regarding mine/non-mine belief in order to determine whether the additional information enabled operators to better discriminate mines from clutter. Using data collected from real landmines, we experimentally investigated which perceptual dimensions most effectively convey different aspects of the information contained in the sensor response to a listener. Results indicated that the presence of metal (detection) could be coded in the fundamental frequency of the audio signal, and that mine/non-mine belief (discrimination), determined using an automated algorithm, could be coded in a separate audio dimension. Operators performed better with this audio coding scheme than one where only metal content information was presented via the fundamental frequency of the audio signal.

Signal processing for improved explosives detection using quadrupole resonance

Quadrupole resonance (QR) technology for explosives detection is of crucial importance in an increasing number of applications. For landmine detection, where the detection system cannot be adequately shielded, QR has proven to be highly effective if the QR sensor is not exposed to radio frequency interference (RFI). However, strong non-Gaussian RFI in the field is unavoidable, making RFI mitigation a critical part of the signal processing. In this paper, a statistical model of the non-Gaussian RFI is presented. The QR model is used within the context of an adaptive filtering methodology to mitigate RFI, and this approach is compared to other RFI mitigation techniques. Results obtained using both simulated and measured QR data are presented.

Enhanced signal and auditory processing for landmine detection using EMI sensors

Although the ability of EMI sensors to detect landmines has improved significantly, false alarm rate reduction remains a challenging problem. However, experienced operators can often discriminate mines from metallic clutter with the aid of an audio transducer. The goal of this work is to optimize the presentation of information to the operator and to determine whether information as to the presence of metal can be co-presented with information regarding mine/non-mine belief. Traditionally, an energy calculation is provided to the sensor operator via a signal whose loudness and/or frequency is proportional to the energy of the received signal. This information codes information as to the amount of metal present. However, there is information in the unprocessed sensor signal that the operator could use to effect discrimination. We have experimentally investigated the perceptual dimensions that most effectively convey the information in a sensor response to a listener using simulated data. Results indicated that, consistent with the auditory warning literature, pulsed audio signals with a distinct harmonic pattern which rise in fundamental frequency can be used to provide information which provides better performance than simple single-frequency tones. Additionally, the data indicated that the amount of metal could be coded in the rising pitch of the complex, and that the mine/no-mine probabilities could be coded in a separate dimension - the pulse rate. In this paper, we describe these results in detail.

Predicting improved human auditory discrimination for land mine detection using EMI sensors

Although the ability of EMI sensors to detect landmines has improved significantly, false alarm rate reduction remains a challenging problem. Improvements have been achieved through development of optimal algorithms that exploit models of the underlying physics along with knowledge of clutter statistics. Moreover, experienced operators can often discriminate mines form clutter with the aid of an audio transducer. Assuming the basic information needed for discriminating landmines form clutter is largely available form existing sensors, the goal of this wok is to optimize the presentation of information to the operator and to be able to predict improved performance prior to extensive experimental testing. Traditionally, an energy calculation is provided to the sensor operator via a signal whose loudness or frequency is proportional to the energy of the received signal Our preliminary theoretical work indicated that when the statistic used to make a decision is not simply the signal energy the performance of mine detection systems can be improved dramatically. This finding suggest that the operator could make better sue of a signal that is a function of this more accurate test statistic, and that there may be information in the unprocessed sensor signal that the operator could use to effect discrimination. We then experimentally investigated the perceptual dimensions that most effectively convey the information in a sensor response to a listener using simulated data. Results indicated that by supplying the sensor response more appropriately to the listener, discrimination, as opposed to simple detection, could be achieved. In this paper we discuss an additional theoretical treatment of these experimental data in which we show that we can predict such improvements. These results are verified in a follow-on listening experiment with actual data measured from landmines.

Enhanced auditory processing for land mine detection using EMI sensors

Although the ability of EMI sensor to detect landmines has improved significantly, false alarm rate reduction remains a challenging problem. Improvements have been achieved through development of optimal algorithms that exploit models of the underlying physics along with knowledge of clutter statistics. Moreover, experienced operators can often discriminate mines from clutter with the aid of an audio transducer, the method most commonly used to alert the sensor operator that a target is presented. Assuming the basic information needed for discriminating landmines from clutter is largely available from existing sensors, the goal of this work is to optimize the presentation of information to the operator. Traditionally, an energy calculation is provided to the sensor operator via a signal whose loudness or frequency is proportional to the energy of the calculation is provided to the sensor operator via a signal whose loudness or frequency is proportional to the energy of the received signal. Our preliminary work has shown that when the statistic used to make a decision is not simply the signal energy the performance of mine detection systems can be improved dramatically. This finding suggests that the operator could make better use of a signal that is a function of this more accurate test statistic, and that there may be information in the unprocessed sensor signal that the operator could use to effect discrimination. In this paper, we investigate and quantify, through listening experiments, the perceptual dimensions that most effectively convey the information in a sensor response more appropriately to the listener, discrimination, as opposed to simple detection, can be achieved.