Optical tweezers have been widely used by biophysicists to measure forces in single molecular processes, such as the force of a motor molecule walking and the force of a DNA molecule winding and unwinding. In these and similar force measurements, the usual assumption is that the force applied to a particle inside the tweezers is proportional to the displacement of the particle away from the trap center like Hookean springs, which would imply that the force field is conservative. However, the Gaussian beam model has indicated that the force field generated by optical tweezers is actually nonconservative, yet no experiments have measured or accounted for this effect. We introduce an experimental method -- the local drift method -- that can measure the force field in optical tweezers with high precision without any assumptions about the functional form of the force field. The force field is determined by analyzing the Brownian motion of a trapped particle. We successfully applied this method to different sizes of particles and measured the three dimensional force field with 10 nm spatial resolution and femtonewton precision in force. We find that the force field is indeed nonconservative. The nonconservative contribution increases radially away from the optical axis for both small and large particles. The curl vector field -- a measurement of the nonconservative force field -- reverses direction from counter-clockwise for small particles in the Rayleigh regime to clockwise for large particles in the ray optics regime, consistent with the different scattering force profiles in the two distinct scattering regimes. Together with the thermal fluctuations of the trapped particle, the nonconservative force can cause a complex flux of energy into the system. Optically-confined Brownian motion is further used to probe nanostructures such as a biopolymer network. This technique -- thermal noise imaging -- uses a Brownian particle as a "natural scanner" to explore a biopolymer network by moving the Brownian particle through the network with optical tweezers. The position fluctuations of the probe particle reflect the location of individual filaments as excluded volumes. The resolution of thermal noise imaging is directly coupled to the size of the probe particle. A smaller probe is capable of exploring smaller pore sizes formed by dense network. Previously, a 200 nm polystyrene particle had been used to probe an agar network. In this work, 100 nm gold probe particles are used to enhance the resolution. A 100 nm particle explore a network with mesh 2³ times smaller and therefore enhance the network resolution by 2³ times. A 100 nm particle also improves the imaging speed by a factor of 2 because of its faster diffusion. Three-dimensional thermal noise images of agarose filaments are obtained and a resolution of 10 nm for the position of the filaments is achieved. In addition, a gold particle is trapped with significantly less power than a polystyrene particle of the same size, indicating the possibility for using even smaller gold particles to further improve the resolution. / text

An approximate of the Green's function can be obtained by taking the cross-correlation of ambient noise that has been simultaneously recorded on separate sensors. This method is applied for two experiments, which illustrate the advantages and challenges of this technique. The first experiment is in the ultrasonic regime [5-30] MHz and uses capacitive micromachined ultrasonic transducer arrays to image the near field and compares the passive imaging to the conventional pulse-echo imaging. Both the array and target are immersed in a fluid with the sensors recording the fluid's random thermal-mechanical motion as the ambient noise. The second experiment is a passive ocean monitoring experiment, which uses spatiotemporal filtering to rapidly extract coherent arrivals between two vertical line arrays. In this case the ambient noise in the frequency band [250 1500] Hz is dominated by non-stationary shipping noise. For imaging purposes, the cross-correlation needs to extract the Green's function so that the imaging can be done correctly. While for monitoring purposes, the important feature is the change in arrivals, which corresponds to the environment changing. Results of both experiments are presented along with the advantages of this passive method over the more accepted active methods.

This thesis presents a body of work on the theme of millimetre-wave FMCW radar, for the purposes of security screening and remote sensing. First, the development of an optimised software radar signal processor will be outlined. Through use of threading and GPU acceleration, high data processing rates were achieved using standard PC hardware. The flexibility of this approach, compared to specialised hardware (e.g. DSP, FPGA etc…), allowed the processor to be rapidly adapted and has produced a significant performance increase in a number of advanced real-time radar systems. An efficient tracker was developed and was successfully deployed in live trials for the purpose of real-time wave detection in an autonomous boat control system. Automated radar operation and remote data telemetry functions were implemented in a terrain mapping radar to allow continuous monitoring of the Soufrière Hills volcano on the Caribbean island of Montserrat. This work concluded with the installation of the system 3 km from the volcano. Hardware modifications were made to enable coherent measurement in a number of existing radar systems, allowing phase sensitive measurements, including range-Doppler, to be performed. Sensitivity to displacements of less than 200 nm was demonstrated, which is limited by the phase noise of the system. Efficient compensation techniques are presented which correct for quadrature mixer imbalance, FMCW chirp non-linearity, and scanner drive distortions. In collaboration with the Home Office, two radar systems were evaluated for the stand-off detection of concealed objects. Automatic detection capability, based on polarimetric signatures, was developed using data gathered under controlled conditions. Algorithm performance was assessed through blind testing across a statistically significant number of subjects. A detailed analysis is presented, which evaluates the effect of clothing and object type on detection efficiency.