Reactive image-based collision avoidance system for unmanned aircraft systems

Approximately 20 years have passed now since the NTSB issued its original recommendation to expedite development, certification and production of low-cost proximity warning and conflict detection systems for general aviation [1]. While some systems are in place (TCAS [2]), ¡¨see-and-avoid¡¨ remains the primary means of separation between light aircrafts sharing the national airspace. The requirement for a collision avoidance or sense-and-avoid capability onboard unmanned aircraft has been identified by leading government, industry and regulatory bodies as one of the most significant challenges facing the routine operation of unmanned aerial systems (UAS) in the national airspace system (NAS) [3, 4]. In this thesis, we propose and develop a novel image-based collision avoidance system to detect and avoid an upcoming conflict scenario (with an intruder) without first estimating or filtering range. The proposed collision avoidance system (CAS) uses relative bearing ƒÛ and angular-area subtended ƒê , estimated from an image, to form a test statistic AS C . This test statistic is used in a thresholding technique to decide if a conflict scenario is imminent. If deemed necessary, the system will command the aircraft to perform a manoeuvre based on ƒÛ and constrained by the CAS sensor field-of-view. Through the use of a simulation environment where the UAS is mathematically modelled and a flight controller developed, we show that using Monte Carlo simulations a probability of a Mid Air Collision (MAC) MAC RR or a Near Mid Air Collision (NMAC) RiskRatio can be estimated. We also show the performance gain this system has over a simplified version (bearings-only ƒÛ ). This performance gain is demonstrated in the form of a standard operating characteristic curve. Finally, it is shown that the proposed CAS performs at a level comparable to current manned aviations equivalent level of safety (ELOS) expectations for Class E airspace. In some cases, the CAS may be oversensitive in manoeuvring the owncraft when not necessary, but this constitutes a more conservative and therefore safer, flying procedures in most instances.

Field-of-view, detection range, and false alarm trade-offs in vision-based aircraft detection

This paper presents a survey of previously presented vision based aircraft detection flight test, and then presents new flight test results examining the impact of camera field-of view choice on the detection range and false alarm rate characteristics of a vision-based aircraft detection technique. Using data collected from approaching aircraft, we examine the impact of camera fieldof-view choice and confirm that, when aiming for similar levels of detection confidence, an improvement in detection range can be obtained by choosing a smaller effective field-of-view (in terms of degrees per pixel).

Airborne collision scenario flight tests : impact of angle measurement errors on reactive vision-based avoidance control

The future emergence of many types of airborne vehicles and unpiloted aircraft in the national airspace means collision avoidance is of primary concern in an uncooperative airspace environment. The ability to replicate a pilot’s see and avoid capability using cameras coupled with vision based avoidance control is an important part of an overall collision avoidance strategy. But unfortunately without range collision avoidance has no direct way to guarantee a level of safety. Collision scenario flight tests with two aircraft and a monocular camera threat detection and tracking system were used to study the accuracy of image-derived angle measurements. The effect of image-derived angle errors on reactive vision-based avoidance performance was then studied by simulation. The results show that whilst large angle measurement errors can significantly affect minimum ranging characteristics across a variety of initial conditions and closing speeds, the minimum range is always bounded and a collision never occurs.

HMM relative entropy rate concepts for vision-based aircraft manoeuvre detection

Machine vision is emerging as a viable sensing approach for mid-air collision avoidance (particularly for small to medium aircraft such as unmanned aerial vehicles). In this paper, using relative entropy rate concepts, we propose and investigate a new change detection approach that uses hidden Markov model filters to sequentially detect aircraft manoeuvres from morphologically processed image sequences. Experiments using simulated and airborne image sequences illustrate the performance of our proposed algorithm in comparison to other sequential change detection approaches applied to this application.

Decision strategies for automated visual collision avoidance

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

Intelligent collision avoidance, control and guidance

This paper reviews a variety of advanced signal processing algorithms that have been developed at the University of Southampton as part of the Prometheus (Programme for European traffic flow with highest efficiency and unprecedented safety) programme to achieve an intelligent driver warning system (IDWS). The IDWS includes the detection of road edges, lanes, obstacles and their tracking and identification, estimates of time to collision, and behavioural modelling of drivers for a variety of scenarios. The underlying algorithms are briefly discussed in support of the IDWS.

Online hidden Markov model parameter estimation and minimax robust quickest change detection in uncertain stochastic processes

Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.

Determination of amines using 2-(11H-benzo[a]carbazol-11-yl) ethyl chloroformate (BCEC-Cl) as labeling reagent by HPLC with fluorescence detection and identification with APCI/MS

A pre-column derivatization method for the sensitive determination of amines using a labeling reagent 2-(11H-benzo[a]-carbazol-11-yl) ethyl chloroformate (BCEC-Cl) followed by high-performance, liquid chromatography with fluorescence detection has been developed. Identification of derivatives was carried out by LC/APCI/MS in positive-ion mode. The chromophore of 1,2-benzo-3,4-dihydrocarbazole-9-ethyl chloroformate (BCEOC-Cl) reagent was replaced by 2-(11H-benzo[a]-carbazol-11-yl) ethyl functional group, which resulted in a sensitive fluorescence derivatizing reagent BCEC-Cl. BCEC-Cl could easily and quickly label amines. Derivatives were stable enough to be efficiently analyzed by HPLC and showed an intense protonated molecular ion corresponding m/z [M+ H](+) under APCI/MS in positive-ion mode. The collision-induced dissociation of the protonated molecular ion formed characteristic fragment ions at m/z 261.8 and m/z 243.8 corresponding to the cleavages of CH2O-CO and CH2-OCO bonds. Studies on derivatization demonstrated excellent derivative yields over the pH 9.0-10.0. Maximal yields close to 100% were observed with three- to four-fold molar reagent excess. In addition, the detection responses for BCEC-derivatives were compared to those obtained using 1,2-benzo-3,4-dihydrocarbazole-9-ethyl chloroformate (BCEOC-Cl) and 9-fluorenyl methylchloroformate, (FMOC-Cl) as labeling reagents. The ratios I-BCEC/I-BCEOC = 1.94-2.17 and I-BCEC/I-FMOC = 1.04-2.19 for fluorescent (FL) responses (here, I was relative fluorescence intensity). Separation of the derivatized amines had been optimized on reversed-phase Eclipse XDB-C-8 column. Detection limits calculated from 0.50 pmol injection, at a signal-to-noise ratio of 3, were 1.77-14.4 fmol. The relative standard deviations for within-day determination (n = 11) were 1.84-2.89% for the tested amines. The mean intra- and inter-assay precision for all amines levels were < 3.64% and 2.52%, respectively. The mean recoveries ranged from 96.6% to 107.1% with their standard deviations in the range of 0.8-2.7. Excellent linear responses were observed with coefficients of > 0.9996. (C) 2006 Elsevier B.V. All rights reserved.

Determination of free fatty acids in soil and bryophyte plants by precolumn derivatization via HPLC with fluorescence detection and tandem mass spectrometry (HPLC-MS/MS)

A sensitive method for the determination of 30 kinds of free fatty acids (FFAs, C-1-C-30) with 1-[2-(p-toluenesulfonate)-ethyl]-2-phenylimidazole-[4,5-f] 9,10-phenan- threne (TSPP) as labeling reagent and using high performance liquid chromatography with fluorescence detection and identification by online postcolumn mass spectrometry with atmospheric pressure chemical ionization (APCI) source in positive-ion mode (HPLC/MS/APCI) has been developed. TSPP could easily and quickly label FFAs in the presence of K2CO3 catalyst at 90 degrees C for 30 min in N,N-dimethylformamide (DMF) solvent, and maximal labeling yields close to 100% were observed with a 5-fold excess of molar reagent. Derivatives were stable enough to be efficiently analyzed by high performance liquid chromatography. TSPP was introduced into fatty acid molecules and effectively augmented MS ionization of fatty acid derivatives and led to regular MS and MS/MS information. The collision induced cleavage of protonated molecular ions formed specific fragment ions at m/z [MH](+)(molecular ion), m/z [M'+CH2CH2](+)(M' was molecular mass of the corresponding FFA) and m/z 295.0 (the, mass of protonated molecular core structure of TSPP). Fatty acid derivatives were separated on a reversed-phase Eclipse XDB-C-8 column (4.6 x 150 mm, 5 mu m, Agilent) with a good baseline resolution in combination with a gradient elution. Linear ranges of 30 FFAs are 2.441 x 10(-3) to 20 mu mol/L, detection limits are 3.24 similar to 36.97 fmol (injection volume 10 mu L, at a signal-to-noise ratio of 3, S/N 3:1). The mean interday precision ranged from 93.4 to 106.2% with the largest mean coefficients of variation (R.S.D.) < 7,5%. The mean intraday precision for all standards was < 6.4% of the expected concentration. Excellent linear responses were observed with correlation coefficients of > 0.9991. Good compositional data could be obtained from the analysis of extracted fatty acids from as little as 200 mg of bryophyte plant samples.Therefore, the facile TSPP derivatization coupled with HPLC/MS/APCI analysis allowed the development of a highly sensitive method for the quantitation of trace levels of short and long chain fatty acids from biological and natural environmental samples.

Analysis of saturated free fatty acids from pollen by HPLC with fluorescence detection

A sensitive method for the determination of free fatty acids using 2-(2-(anthracen-10-yl)-1H-naphtho[2,3-dimidazol-1-yl) ethyl-p-toluenesuIfonate (ANITS) as tagging reagent with fluorescence detection has been developed. ANITS could easily and quickly label fatty acids in the presence of the K2CO3 catalyst at 90 degrees C for 40 min in N,N-dimethylformamide solvent. From the extracts of rape bee pollen samples, 20 free fatty acids were sensitively determined. Fatty acid derivatives were separated on a reversed-phase Eclipse XDB-C8 column by HPLC in conjunction with gradient elution. The corresponding derivatives were identified by post-column APCI/MS in positive-ion detection mode. ANITS-fatty acid derivatives gave an intense molecular ion peak at mlz [M+H](+); with MS/MS analysis, the collision-induced dissociation spectra of m/z [M+H](+) produced the specific fragment ions at mlz [M-345](+) and mlz 345.0 (here, m/z 345 is the core structural moiety of the ANITS molecule). The fluorescence excitation and emission wavelengths of the derivatives were lambda(ex) = 250 nm and lambda(em) = 512 nm, respectively. Linear correlation coefficients for all fatty acid derivatives are > 0.9999. Detection limits, at a signal-to-noise ratio of 3 : 1, are 24.76-98.79 fmol for the labeled fatty acids.

Development of a sensitive fluorescent derivatization reagent 1,2-benzo-3,4-dihydrocarbazole-9-ethyl chloroformate (BCEOC) and its application for determination of amino acids from seeds and bryophyte plants using high-performance liquid chromatography with fluorescence detection and identification with electrospray ionization mass spectrometry

A pre-column derivatization method for the sensitive determination of amino acids and peptides using the tagging reagent 1,2-benzo-3,4dihydrocarbazole-9-ethyl chloroformate (BCEOC) followed by high-performance liquid chromatography with fluorescence detection has been developed. Identification of derivatives was carried out by liquid chromatography/electrospray ionization mass spectrometry (LC/ESI-MS/MS). The chromophore of 2-(9-carbazole)-ethyl chloroformate (CEOC) reagent was replaced by 1,2-benzo-3,4-dihydrocarbazole functional group, which resulted in a sensitive fluorescence derivatizing reagent BCEOC. BCEOC can easily and quickly label peptides and amino acids. Derivatives are stable enough to be efficiently analyzed by high-performance liquid chromatography. The derivatives showed an intense protonated molecular ion corresponding m/z (M + H)(+) under electrospray ionization (ESI) positive-ion mode with an exception being Tyr detected at negative mode. The collision-induced dissociation of protonated molecular ion formed a product at m/z 246.2 corresponding to the cleavage of C-O bond of BCEOC molecule. Studies on derivatization demonstrate excellent derivative yields over the pH 9.0-10.0. Maximal yields close to 100% are observed with a 3-4-fold molar reagent excess. Derivatives exhibit strong fluorescence and extracted detzvatization solution with n-hexane/ethyl acetate (10:1, v/v) allows for the direct injection with no significant interference from the major fluorescent reagent degradation by-products, such as 1,2-benzo-3,4-dihydrocarbazole-9-ethanol (BDC-OH) (a major by-product), mono- 1,2-benzo-3,4-dihydrocarbazole-9-ethyl carbonate (BCEOC-OH) and bis-(1,2-benzo-3,4-dihydrocarbazole-9-ethyl) carbonate (BCEOC)(2). In addition, the detection responses for BCEOC derivatives are compared to those obtained with previously synthesized 2-(9-carbazole)-ethyl chloroformate (CEOC) in our laboratory. The ratios AC(BCEOC)/AC(CEOC) = 2.05-6.51 for fluorescence responses are observed (here, AC is relative fluorescence response). Separation of the derivatized peptides and amino acids had been optimized on Hypersil BDS C-18 column. Detection limits were calculated from 1.0 pmol injection at a signal-to-noise ratio of 3, and were 6.3 (Lys)-177.6 (His) fmol. The mean interday accuracy ranged from 92 to 106% for fluorescence detection with mean %CV < 7.5. The mean interday precision for all standards was < 10% of the expected concentration. Excellent linear responses were observed with coefficients of > 0.9999. Good compositional data could be obtained from the analysis of derivatized protein hydrolysates containing as little as 50.5 ng of sample. Therefore, the facile BCEOC derivatization coupled with mass spectrometry allowed the development of a highly sensitive and specific method for the quantitative analysis of trace levels of amino acids and peptides from biological and natural environmental samples. (c) 2005 Elsevier B.V. All rights reserved.

An FLIR video surveillance system to avoid bridge-ship collision

In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image pre-processing algorithm is proposed to reduce clutter noises by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers

A bridge-ship collision avoidance system based on FLIR image sequences

In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image preprocessing algorithm is proposed to reduce clutter background by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. When the moving ships are detected in region of surveillance, the device for safety alert is triggered. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers.

ASSESSMENT of POLYATOMIC INTERFERENCES ELIMINATION USING A COLLISION REACTION INTERFACE (CRI) FOR INORGANIC ANALYSIS of FUEL ETHANOL BY ICP-QMS

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)