Radiation monitoring method and circuitry

Abstract

A radiation monitoring method comprising: receiving radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; detecting a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation; determining, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative an intensity of radiation detected by the radiation detector; and correlating the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

Description

[0001] P131127GB

[0002] RADIATION MONITORING METHOD AND CIRCUITRY

[0003] Field of the Disclosure

[0004] The present disclosure relates to radiation monitoring methods, apparatuses, circuitry, and software.

[0005] Description of the Related Art

[0006] The “background” description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in the background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of filing, are neither expressly or impliedly admitted as prior art against the present disclosure.

[0007] There is currently a widespread use of radiation monitoring apparatuses at locations such as points of entry (POE) between countries, and in other locations where monitoring of objects for potential sources of radiation is of interest. Radiation monitoring apparatuses include radiation portal monitors (RPMs) for monitoring nuclear radiation emission from both containerised and non-containerised cargo, including vehicular freight and rail-freight , in order to detect undeclared radioactive materials concealed in cargo. In particular, such RPMs may serve to help detect the presence of illicit Special Nuclear Materials (SNM). RPMs typically comprise a number of radiation detectors (e.g. gamma-ray and I or neutron detectors) through which nuclear materials, and SNMs in particular, can be detected and classified based on the radiation emitted by such materials. Radiation monitoring apparatuses can also be configured for monitoring for radiation emission from pedestrians, animals, and other objects. For example, pedestrian radiation monitoring apparatuses can be set up in locations such as airports and rail terminals to monitor pedestrians for sources of radiation emission. Radiation monitoring apparatuses may also be configured to monitor baggage and other objects in such locations. It will be appreciated radiation monitoring apparatuses, such as RPMs and pedestrian radiation monitoring apparatuses, but more generally any radiation monitoring apparatus class referred to herein, may be provided as a ‘deployable’ radiation monitoring apparatus, which may be transported to a site for temporary or semipermanent use, as opposed to a ‘fixed’ radiation monitoring apparatus which is designed to remain permanently in one location during its operation.

[0008] Mobile radiation identification devices are another class of radiation monitoring apparatus in current usage, comprising sub-classes such as (i) handheld, (ii) backpack, and (iii) vehiclemounted radiation monitoring apparatuses, configured for mobile deployment to areas of interest. Mobile radiation monitoring devices may be used to provide complementary functionality to fixed or semi-fixed (e.g. so-called ‘deployable’) radiation monitoring apparatuses such as RPMs. Thus,P131127GB

[0009] for example, personnel at a site where one or more RPMs are installed for vehicular inspection may use one or more mobile radiation monitoring apparatuses (e.g. nuclear radiation monitoring apparatuses) to conduct investigations of vehicles which have been identified as presenting a potential risk based on (nuclear) radiation monitoring conducted by an RPM.

[0010] Forms of radiation of interest for monitoring by radiation monitoring control logic as described herein may comprise nuclear radiation, but may more generally comprise any particle, electromagnetic, or acoustic radiation.

[0011] Where a radiation detector of a radiation monitoring apparatus detects radiation, it may be evident which of one or more objects and I or systems within detection range of the radiation detector is responsible for the emission. For example, a radiation monitoring apparatus may be provided with a monitoring region where a single object can be positioned for monitoring, isolated from other objects, in a context where radiation shielding substantially or totally prevents radiation emitted from outside the monitoring region from reaching a radiation detector of the apparatus. In such a scenario, it may be reasonably assumed that a single object within the monitoring region is substantially responsible for any non-background radiation detected at the radiation detector, and that the object is thus a radiation emitter (i.e. comprises a radiation source). However, in many radiation monitoring contexts, such assumptions cannot be made. For example, where a radiation detector is positioned to monitor a monitoring region (e.g. a pathway or concourse) through which pedestrians are free to transit, there may be plural pedestrians and I or other objects within detection range of the radiation detector at any point in time. In such a context, when a radiation detector of such an apparatus detects incident radiation, the issue arises of determining which one or more objects in a monitoring region is associated with emission of any detected radiation. Approaches to assist in identification of sources of radiation detected by radiation detectors of radiation monitoring apparatuses are thus of interest.

[0012] SUMMARY

[0013] According to a first aspect of the present disclosure, there is provided a radiation monitoring method comprising: receiving radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; detecting a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation; determining, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative an intensity of radiation detected by the radiation detector; and correlating theP131127GB

[0014] detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

[0015] According to a second aspect of the present disclosure, there is provided a non-transitory computer program product configured to control a computer to perform a method according to the first aspect.

[0016] According to a third aspect of the present disclosure, there is provided a recording medium storing a non-transitory computer program product according to the second aspect.

[0017] According to a fourth aspect of the present disclosure, there is provided radiation monitoring circuitry comprising control logic configured to: receive radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; detect a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation; determine, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of an intensity of radiation detected by the radiation detector; and correlate the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

[0018] According to a fifth aspect of the present disclosure, there is provided a radiation monitoring apparatus comprising the radiation monitoring circuitry of the fourth aspect, further comprising the radiation detector.

[0019] According to a sixth aspect of the present disclosure, there is provided a radiation monitoring apparatus according to the fifth aspect, further comprising an object position sensing system configured to transmit object position data to the radiation monitoring circuitry, wherein the object position data is indicative of positioning of each of the one or more objects within the region from which the radiation detector is configured to receive radiation, wherein the control logic is configured to detect the change in the spatial position of each object based on the object position data.

[0020] The described embodiments, together with further advantages, will be best understood by reference to the following detailed description taken in conjunction with the accompanying drawings.

[0021] BRIEF DESCRIPTION OF THE DRAWINGSP131127GB

[0022] A more complete appreciation of the disclosure and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings, wherein:

[0023] Figure 1 schematically shows a radiation monitoring apparatus according to embodiments of the present disclosure;

[0024] Figure 2 schematically shows the radiation monitoring apparatus of Figure 1 in the context of a first configuration of objects within a region from which a radiation detector of the radiation monitoring apparatus is configured to receive radiation;

[0025] Figure 3 schematically shows a spectrum of radiation detected by a radiation detector, associated with the configuration of objects in Figure 2;

[0026] Figure 4 schematically shows the radiation monitoring apparatus of Figure 1 in the context of a second configuration of objects within a region from which a radiation detector of the radiation monitoring apparatus is configured to receive radiation;

[0027] Figure 5 schematically shows respective spectra of radiation detected by a radiation detector, associated with the respective configurations of objects in Figures 2 and 4;

[0028] Figure 6 schematically shows radiation monitoring control logic according to embodiments of the present disclosure;

[0029] Figure 7 schematically shows a processing flow associated with modules of radiation monitoring control logic according to embodiments of the present disclosure;

[0030] Figures 8 and 9 schematically shows aspects of an approach for detecting a change in spatial position of an object within a region from a radiation detector is configured to receive radiation; Figures 10A to 10C shows schematically aspects of determination of solid angles subtended by objects at a radiation detector location;

[0031] Figure 11 shows schematically a spectrum of radiation detected by a radiation detector, indicating different sub-ranges from within an overall range of detection energy;

[0032] Figure 12 schematically shows a visualisation of a plurality of representations of objects in a scene, comprising labels indicating object type, a correlation parameter, and a type of radiation source;

[0033] Figure 13 is a flow chart schematically showing steps of a method according to embodiments of the present disclosure.P131127GB

[0034] DESCRIPTION OF THE EMBODIMENTS

[0035] Referring now to the drawings, wherein like reference numerals designate identical or corresponding parts throughout the several views, embodiments of the present disclosure are described in detail.

[0036] The present technique relates to methods, control logic (e.g. circuitry and I or software), and I or apparatuses for correlating a detected change in a spatial position of each of one or more objects within a region from which a radiation detector is configured to receive radiation, with a change in a radiation intensity parameter determined based on radiation data generated by the radiation detector. For the purposes of describing approaches according to the present disclosure in the context of a concrete use case, these methods, control logic (e.g. circuitry and I or software), and I or apparatuses will typically be described herein as being associated with a radiation monitoring apparatus comprising a radiation detector. A radiation monitoring apparatus for monitoring pedestrian traffic for the presence of radiation sources is used herein as an illustrative example of a radiation monitoring apparatus, with which approaches according to the embodiments herein may be used. However, it will be appreciated that a radiation monitoring apparatus for monitoring pedestrian traffic is only one embodiment of a radiation monitoring apparatus with which methods according to the present disclosure can be implemented, and control logic (e.g. circuitry and I or software), implementing methods of the present disclosure are suitable for use with any known class of radiation monitoring apparatus.

[0037] Nuclear radiation monitoring apparatuses comprising at least one gamma and I or neutron radiation detector are a particular use case described herein for the purpose of providing a concrete example. However, it will be appreciated a radiation monitoring apparatus suitable for use with any of the methods and control logic (e.g. circuitry and I or software) described herein, may comprise any radiation detector configured for detecting any form of radiation, and thus, by way of non-limiting examples, may comprise any of: a particle radiation detector configured for detecting alpha (a), beta (P), proton, or any other particle radiation; a radio detector configured for detecting radio wave radiation; a microwave detector configured for detecting microwave radiation; an infra-red (IR) detector configured for detecting IR radiation; a visible light detector configured for detecting radiation in the human-visible portion of the electromagnetic spectrum; an ultraviolet (UV) detector configured for detecting UV radiation; an X-ray detector configured for detecting X-ray radiation; a gravitational wave detector for detecting gravitational waves; or an acoustic detector configured for detecting sound waves. More generally, ‘radiation’ as referred to herein may comprise any form of propagating energy (e.g. particles and waves emitted into space), for which an intensity at a point or region may be characterised by a suitable sensor.P131127GB

[0038] It will be appreciated the approaches described herein are suitable for use in the context of both static and mobile radiation monitoring apparatuses. Thus a radiation monitoring apparatus comprising at least one radiation detector, with which methods and control logic (e.g. circuitry and I or software) according to the present disclosure may be used include static radiation monitoring apparatuses such as:

[0039] • radiation portal monitors (RPMs) for monitoring of containerised or non-containerised cargo, and I or vehicles such as trucks, cars, trains, or ships, particularly but not exclusively at points of entry (POE) to countries and I or secure sites such as nuclear facilities;

[0040] • pedestrian radiation monitors for monitoring regions associated with pathways, concourses, and other areas of pedestrian footfall at POEs such as airports and railway stations, leisure sites such as sports stadiums, and secure sites such as embassies or military bases;

[0041] • cargo I baggage radiation monitors for monitoring regions associated with transit of cargo I baggage, such as cargo I baggage transiting a conveyor belt system or being manoeuvred with human or vehicular assistance in a context such as a depot, distribution centre, postal sorting office, or freight handling centre;

[0042] • highway traffic monitors for monitoring regions comprising one or more roadways I highways along which vehicular traffic is configured to pass.

[0043] Alternatively, a radiation monitoring apparatus comprising at least one radiation detector, with which methods and control logic (e.g. circuitry and I or software) according to the present disclosure may be used include mobile radiation monitoring apparatuses such as: (i) handheld, (ii) backpack, and (iii) vehicle mounted devices. Accordingly, any reference herein to a pedestrian radiation monitoring apparatus can be substituted for any other class of static or mobile radiation monitoring apparatus comprising at least one radiation detector. More generally, the skilled person will appreciate from the present disclosure that methods according to the present disclosure, and software and I or circuitry implementing control logic for carrying out such methods, can be used in any other contexts where it is of interest to the skilled person to correlate a detected change in a spatial position of each of one or more objects within a region from which a radiation detector is configured to receive radiation, with a determined change in a radiation intensity parameter indicative of a change in an intensity of radiation detected by the radiation detector.

[0044] Thus, the present disclosure details circuitry, software, and methods, for performing such a correlation in a manner that is agnostic to any specific type of radiation detector, radiation monitoring apparatus, or wider use context.P131127GB

[0045] Figure 1 shows an exemplary radiation monitoring apparatus 1 with which methods, software, and I or circuitry may be implemented according to embodiments of the present disclosure. The radiation monitoring apparatus 1 comprises a radiation detector system 100, which in this example comprises a gamma radiation detector 100A and a neutron radiation detector 100B. It will be appreciated a single radiation detector might be included in the radiation detector system 100 other contexts, and that the specific number of detectors, and the type of radiation they are configured to detect, is not of particular significance to the general approach set out herein. In radiation monitoring apparatus 1, the gamma radiation detector 100A and a neutron radiation detector 100B are associated with a region 105 from which the each of the radiation detectors (and by extension the radiation detector system 100) is configured to receive radiation. It will be appreciated the extent of this region will be defined by factors such as the design of the specific radiation detectors used, the type of radiation they are configured to detect, and environmental aspects such as the topology and atmospheric conditions of the context in which the radiation detector system 100 is situated. In the example of Figure 1, the radiation monitoring apparatus 1 is configured as a pedestrian radiation monitoring apparatus, and the gamma radiation detector 100A and a neutron radiation detector 100B are configured to receive radiation from at least a spatial region 105 (noting the actual extent of the region over which radiation may be received may extend beyond the region 105). The region 105 may also be referred to herein as a monitoring region for one or both of the gamma radiation detector 100A and a neutron radiation detector 100B. Each radiation detector of a plurality of radiation detectors may have its own region (i.e. monitoring region) 105 from which it is configured to receive radiation, or plural radiation detectors may share the same monitoring region 105 from which they are configured to receive radiation.

[0046] Gamma and neutron radiation detectors are instruments that respond, respectively, to gammarays and neutron emissions emanating from both target objects being monitored I assessed (e.g. a pedestrian or other object passing through the monitoring region 105) and the surrounding environment. Each gamma radiation detector 100A, where present, may be configured to record data indicative of an energy-loss spectrum, and / or a total intensity spectrum, of gamma radiation (either of which may be referred to as a ‘gamma-ray spectrum’) over a given time interval. This data can be referred to as gamma radiation data, and is a sub-set of radiation data as described herein. Each of one or more gamma radiation detectors 100A may be, for example, a plastic scintillator detector (in particular, a polyvinyl-toluene scintillator detector), a garnet ceramic scintillator detector (and I or other detectors known to the skilled person based on garnet and I or ceramic technology), a crystal scintillator detector, solid state detector, silicon detector, cadmium zinc telluride (CZT) detector, high purity germanium (HPGe) detector, proportional gas counter, or any other gamma radiation detector known to the skilled-person. The output of each gamma radiation detector 100A will typically comprise a rate of detection events (referred to herein as aP131127GB

[0047] ‘count rate’ or ‘detection count rate’), typically segregated into ranges of detection energy (expressed for example in KeVs), such that separate count rates can be discriminated for different sub-ranges of energy across a detectable range, enabling computation of a spectrum. The detectable energy range and noise floor of count rate will be a function of the particular detector design, and differs across different detector types. The determination of count rates associated with different detection energy levels is typically achieved using multi-channel analyser (MCA) control logic, implemented in hardware and I or software, connected to radiation detector hardware, and configured to process voltage pulses generated by each of one or more gamma radiation detectors 100A in response to excitation by incident radiation, converting them to a representation of count rate with respect to ranges of incident energy. MCA control logic may be integrated into a gamma radiation detector unit 100A, such that each gamma radiation detector (or panel) comprises an inbuilt MCA which analyses the raw data from each detector and returns radiation data comprising an indication of detection event count rate with respect to energy. Alternatively an MCA may be implemented as a standalone module of control logic configured to receive raw radiation data generated by one or more gamma radiation detectors 100A of a radiation monitoring apparatus (such as the pedestrian radiation monitoring apparatus 1 of Figure 1), and configured to pass processed radiation data to radiation monitoring control logic 190 configured to perform further processing steps such as classifying detected radiation using the radiation data to identify at least one radioactive isotope comprised in a target object from which the detected radiation is received. In other embodiments, MCA functionality may be integrated into radiation monitoring control logic 190 of a radiation monitoring apparatus 1, as shown in Figure 6. However, it will be appreciated herein that use of an MCA in analyser control logic is not essential, and that in some embodiments, particularly where the radiation intensity parameter is a detected count rate, a single-channel analyser (SCA) may be used, configured to provide a radiation intensity parameter for a single window of energy or frequency, based on raw output from one or more radiation detectors. Thus though reference may be made to ‘MCA I analyser control logic’ herein, this may be substituted for ‘SCA I analyser control logic’, for embodiments where intensity is not quantified in parallel for multiple channels (i.e. discrete ranges) of detection energy or frequency (e.g. embodiments where the radiation intensity parameter comprises a detection count rate for a single range of energy or frequency).

[0048] It will be appreciated that the functionality of MCA I analyser control logic, and indeed any of the control logic or ‘circuitry’ described herein, may be implemented as hardware control logic (e.g. one or more application specific integrated circuit (ASIC) or field programmable gate array (FPGA) modules), or may be implemented as one or more modules of software running on processor circuitry of a general purpose computing device, configured to process commands via one or more CPU and I or GPU modules. Thus the MCA I analyser control logic may be implemented as and referred to as either a hardware analyser, or a software analyser. In Figure 1, (nuclear)P131127GB

[0049] radiation monitoring control logic 190 is shown, which as discussed further herein can, in embodiments, integrate one or more of the functions which are herein associated with MCA I analyser control logic, radiation classifier control logic, object position determiner control logic, correlator control logic, visualisation data generator control logic, and indeed any other control logic I circuitry described herein.

[0050] Similar to the gamma radiation detector described above, each neutron radiation detector 100B, where present, is configured to record data indicative of a flux of incident neutrons over a given time interval. This data may be referred to as neutron data, and is a specific subset of radiation data. The raw sensor output of one or more neutron radiation detectors 100B may, in a similar manner to the sensor output of one or more gamma radiation detectors, be processed by one or more modules of MCA I analyser control logic to discriminate count rates by incident energy. Suitable gamma and neutron radiation detectors for (nuclear) radiation monitoring apparatuses are known in the art and are therefore not discussed further in detail here.

[0051] In the context of the pedestrian radiation monitoring apparatus 1 of Figure 1, each of the radiation detectors (100A, 100B) is in data communication with radiation monitoring control logic 190 so as to allow the generated radiation data to be provided to the radiation monitoring control logic 190. This data transmission between each radiation detector and the radiation monitoring control logic 190 is achieved using wired or wireless data communication approaches known to the person skilled in the art. A user-feedback apparatus 191 (e.g. monitor comprising a liquid crystal display (LCD) or similar for displaying images, and / or a speaker module for providing audible alarms) may be connected to the radiation monitoring control logic to enable the radiation monitoring control logic 190 to provide feedback to a user.

[0052] Figure 1 further shows two pedestrians 1021 and 1022 in side view. The pedestrians 1021 and 1022 are examples of objects within a region (i.e. monitoring region) 105 from which the radiation detector system 100 (here comprising gamma radiation detector 100A and neutron detector 100B) is configured to receive radiation. As discussed further herein, pedestrians are a nonlimiting use case, and any object which represents a potential source of radiation emission may be considered an ‘object’ according to the present disclosure. Here the radiation detector system is configured to receive at least gamma and neutron radiation, though the particular type of radiation will depend on the configuration of radiation detector system 100 and constituent radiation detector(s)). The view shown in Figure 1 is at a first time point, ti, at which the pedestrians 1021 and 1022 are at respective distances along the x axis of xti, 2i and xti, 1022 from a front face of the radiation detector system 100.

[0053] Figure 2 shows a top view of the pedestrian radiation monitoring apparatus 1 of Figure 1, in plan view. The radiation detector system 100 is shown, comprising a gamma radiation detector 100AP131127GB

[0054] and neutron radiation detector 100B as described in relation to Figure 1. In the exemplary pedestrian radiation monitoring apparatus 1 the gamma radiation detector 100A is positioned above the neutron radiation detector 100B, so that in a top-down schematic view of Figure 2 the two detectors can be considered to be overlapping. However, it will be appreciated where plural radiation detectors are provided, these can be arranged in different configurations (e.g. side by side). Figure 2 shows the monitoring region 105 from which the gamma and neutron radiation detectors (100A, 100B) are configured to receive radiation. In the top-down view of Figure 2, this region is seen to have a viewing angle, which may be defined by collimation and I or shielding of one or more detector elements each radiation detector. In the example of Figure 2, the azimuthal viewing angle of the radiation detectors, which defines the angular extent of the monitoring region 105 around the y axis shown in Figure 1, is roughly 2TT / 3 radians. However, it will be appreciated different azimuthal viewing angles may be configured for different radiation detectors I radiation detector systems, defining different angular extents of monitoring region 105. In other examples, the azimuthal viewing angle may be, for example, 2TT, or take a value in the range 0 to TT / 6, or TT / 6 to TT / 3, or TT / 3 to TT / 2, or TT / 2 to TT, or TT to 7TT / 6, or 7TT / 6 to 4TT / 3, or 4TT / 3 to 3TT / 2, or 3TT / 2 to 2TT. Figures 1 and 2 both show a scenario at a first time point, ti , at which pedestrians 1021 and 1022 within the monitoring region 105 are at respective absolute distances dti,io2i and dti, 1022 from a reference location 110 having a fixed relationship to the gamma radiation detector 100A, being positioned here on a front face of the radiation detector system 100.

[0055] Figure 3 shows schematically a plot of radiation intensity detected by one of the radiation detectors of the radiation detector system 100. For the sake of explanation, it may be assumed that Figure 3 shows an exemplary plot of detection rate (in terms of counts) for each of a plurality of sub-ranges of detection energy (in KeV) of radiation received at the gamma radiation detector 100A, as generated from raw output of the gamma radiation detector 100A by MCA I analyser control logic using approaches described further herein. Such a plot of radiation intensity may be referred to herein as a spectrum, and it will be appreciated such plots and approaches to their generation from raw radiation output from a radiation detector are known to the skilled person. For example a raw spectrum or processed spectrum (e.g. a spectrum processed via an approach such as spectral deconvolution, as described in [3] and [4]) may be used. However, in other scenarios, other measures of radiation intensity, and / or forms of representing radiation intensity, may be used. In some embodiments, a radiation intensity parameter may simply comprise a total number of counts over one or more capture intervals for the radiation detector 100A, as generated, for example, by analyser circuitry based on raw radiation detector output. In other examples, a heat map of radiation intensity might be generated based on output from a radiation detector 100A comprising a one, two, or higher dimensional array of discrete detector elements, allowing spatial reconstruction of radiation intensity measured at different points I regions in space. Such a heat map may comprise a one-dimensional, two-dimensional, or higher-P131127GB

[0056] dimensional image, wherein an intensity value for each portion of the image (i.e. a radiation intensity parameter) is proportional to a radiation intensity measured by a corresponding one or more of a plurality of discrete detector elements over one or more capture intervals.

[0057] The spectrum shown in Figure 3 relates to a first time point ti , which here can be considered to be an end-time of a capture interval to which the radiation data used to generate the spectrum relates. The exemplary spectrum comprises characteristic peaks 201 and 202. As known to the skilled person, and as described further herein, classifier control logic can be configured to determine, from a spectrum, one or more radiation sources (e.g. materials such as radioisotopes, and I or radiation-emitting devices) associated with emission of radiation detected by a radiation detector responsible for generating radiation data from which said spectrum was derived. Thus, as known to the skilled person, suitable classifier control logic can be configured to determine from radiation data obtained from a radiation detector, both that a radiation source is present within a monitoring region of the radiation detector, and potentially to determine the type of source. However, the identification of which of a plurality of objects within the monitoring region of the radiation detector comprises or contains such a radiation source may present a challenge. For example, in Figures 1 and 2, which show positions of objects (pedestrians) 1021 and 1022 at a first time ti , it cannot be determined from the spectrum of Figure 3 alone whether one, both, or neither, of the objects 1021 and 1022 is associated with the emission of gamma radiation to which the spectrum of Figure 3 relates, despite this spectrum being associated with time ti. This lack of discrimination between different objects may be problematic, since at locations (e.g. POEs) where radiation monitoring apparatuses such as pedestrian radiation monitoring apparatus 1 are implemented, it is typically of interest not only to identify that a radiation source is present, but to identify which of one or more candidate objects (e.g. pedestrians, animals, cargo, vehicles) in a monitoring region is most likely to be associated with the source, so that the object(s) can be apprehended for further assessment I searching.

[0058] The inventors have recognised that the identification of one or more objects likely to be responsible for emission of radiation detected by a radiation detector can be facilitated by monitoring the spatial position of said object(s) during a period of time over which radiation data is obtained by the radiation detector, and correlating changes in characteristics of the radiation data to changes in spatial position of the object(s). Thus, there is disclosed herein a radiation monitoring method comprising: receiving radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; detecting a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation; determining, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensityP131127GB

[0059] parameter being indicative of an intensity of radiation detected by the radiation detector; and correlating the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

[0060] There is further disclosed herein radiation monitoring circuitry comprising control logic configured to: receive radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; detect a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation; determine, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of a an intensity of radiation detected by the radiation detector; and correlate the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

[0061] There is further disclosed herein a radiation monitoring apparatus comprising such radiation monitoring circuitry, and further comprising the radiation detector.

[0062] There is further disclosed herein a radiation monitoring apparatus, with or without a radiation detector, further comprising an object position sensing system configured to transmit object position data to the radiation monitoring circuitry, wherein the object position data is indicative of positioning of each of the one or more objects within the region from which the radiation detector is configured to receive radiation, wherein the control logic is configured to detect the change in the spatial position of each object based on the object position data.

[0063] It will be understood that any method steps described herein can be implemented by control logic embodied as hardware control logic (e.g. one or more application specific integrated circuit (ASIC) or field programmable gate array (FPGA) modules), or may be implemented as one or more modules of software running on processor circuitry of a general purpose computing device, configured to process commands via one or more CPU and I or GPU modules.

[0064] Figure 4 shows a view of the same pedestrian radiation monitoring apparatus 1 as shown in Figure 2, but at a second, subsequent time t2, at which the positions of the pedestrians 1021 and 1022 within the (monitoring) region 105 from which the radiation detector is configured to receive radiation, have changed. This is due to movement, between times ti and t2, of pedestrian 1021 along path P1021, and of pedestrian 1022 along path P1022. Consequently, at time point, ti, the pedestrians 1021 and 1022 within the monitoring region 105 are at respective distances dt2,io2i and dt2, 1022 from the reference location 110. Comparing the spatial configuration of the pedestrians 1021 and 1022 to the pedestrian radiation monitoring apparatus 1 at time ti (as shown in FigureP131127GB

[0065] 2) to the configuration at time t2, it is observed pedestrian 1021 has moved closer to the evaluation location 110 by a distance corresponding to:

[0066] ^t2-tl,1021 — ^t2,1021 dtl,1021>

[0067] and that pedestrian 1022 has moved away from the evaluation location 110 by a distance corresponding to:

[0068] ^t2-tl,1022=^t2,1022—^tl,1022 >

[0069] Figure 5 will be recognised from Figure 3, and shows the same spectrum (radiation intensity plot) generated by MCA I analyser circuitry based on radiation data obtained from the gamma radiation detector 100A at time ti , but also shows, in solid line, a spectrum generated by MCA I analyser circuitry based on radiation data obtained from the gamma radiation detector 100A at subsequent time t2. Across the range of detection energy, it is observed that the plot of radiation intensity (i.e. counts) is elevated at t2as compared to ti , indicating a greater intensity of detected radiation at the gamma radiation detector 100A at time t2 as compared to time ti. A radiation intensity parameter, determined based on radiation data obtained from the gamma radiation detector 100A, may be quantified by, for example, integrating under the spectrum of radiation intensity (i.e. counts) over the detection range of the gamma radiation detector 100A, or by integrating under the spectrum in one or more sub-ranges (such as sub-range Ea) where each sub-range spans less than the overall detection range of the gamma radiation detector 100A, or by identifying a count rate associated with each of one or more discrete energy levels within the spectrum. In some embodiments, the radiation intensity parameter comprises a radiation intensity associated with a combination of energy ranges distinguishing a specific, known radio-isotope. More generally, a radiation intensity parameter may be any measure of radiation intensity known to the skilled person, and may or may not be associated with characteristics (e.g. spectral characteristics) of a particular type of radiation source, such as a type of material (e.g. radioisotope) or radiation emitting device. Determining a change in any of these radiation intensity parameters comprises calculating the difference in said parameter between the first time point ti and the second time point t2. It will be appreciated that any of these exemplary radiation intensity parameters may be observed to increase or decrease between ti and t2, based on the gamma radiation spectra for each of these time points. An increase in measured radiation intensity is shown across the whole detected energy range in the schematic example of Figure 5, but as described further herein, it may be the case that between two given times ti and t2, radiation intensity decreases across the whole detected energy range, or it may increase over one or more sub-range(s) and decrease over one or more sub-range(s). As described further herein, the latter scenario is shown schematically in Figure 11.P131127GB

[0070] Thus, over the period from ti to t2, a radiation intensity parameter indicative of a change in an intensity of radiation detected by the gamma radiation detector 100A (e.g. the area under the radiation intensity spectrum) increases, as the pedestrian 1021 moves towards the gamma radiation detector 100A, and the pedestrian 1022 moves away from the gamma radiation detector 100A. As the skilled person recognises, the observed intensity of radiation at an evaluation location (e.g. at a gamma radiation detector 100A) is, in an ideal case, inversely proportional to the square of the distance from the radiation source to the evaluation location. Thus, assuming a gamma radiation source responsible for radiation detected by the gamma radiation detector 100A has a substantially constant activity (i.e. the rate of gamma radiation emission from the surface of the source does not vary substantially between times ti and t2), an increase in detected radiation intensity at the gamma radiation detector 100A can be assumed to result from at least one source within the monitoring region 100A moving towards the gamma radiation detector 100A between times ti and t2. Correlating the changes in spatial position of pedestrians 1021 and 1022, observed in Figure 4, with the change in radiation intensity observed in Figure 5, thus allows determination of pedestrian 1021 as the most likely object, from between pedestrians 1021 and 1022, to be responsible for the gamma radiation detected by the gamma radiation detector 100A at times ti and t2. It will be appreciated this does not preclude one or more further objects in the monitoring region from being emitters of radiation detected by the radiation detector 100A. For example, in the example of Figures 4 and 5, pedestrians 1021 and 1022 might both comprise sources of gamma radiation, with their respective changes of position between times ti and t2, shown schematically in Figure 4, leading to the increase in radiation intensity observed in the spectra of Figure 5. This might be the case if, for example, pedestrians 1021 and 1022 both comprise radiation sources of the same type, but pedestrian 1021 (who moves towards the radiation detector 100A between ti and t2) carries a source of higher activity than pedestrian 1022 (who moves away from the radiation detector 100A over the same period). It will also be appreciated that in other scenarios, there may be no object within the monitoring region whose change in spatial position has an observable correlation with an observed change in a radiation intensity parameter determined based on output from the radiation detector. In this latter case, it may still be useful to be able to exclude (to a certain level of probability), one or more objects from likely association with emission of radiation detected by the radiation detector, by determining a low or absent correlation between their change in spatial position and the change in radiation intensity parameter.

[0071] Methods, control logic (i.e. hardware and I or software), and apparatuses are now described in more detail, configured for receiving radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; detecting a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector isP131127GB

[0072] configured to receive radiation; determining, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of an intensity of radiation detected by the radiation detector; and correlating the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

[0073] Figure 6 schematically shows radiation monitoring control logic 190 which can be configured to perform methods and I or aspects of methods according to embodiments of the present disclosure. The radiation monitoring control logic 190 shown in Figure 6 is described here in the context of a configuration for use with a pedestrian radiation monitoring apparatus 1 as shown schematically in Figures 1, 2 and 4, but it will be appreciated it can be used with appropriate modifications in the context of any other radiation monitoring apparatus as described further herein. The exemplary radiation monitoring control logic 190 comprises the following submodules: a communication interface 1901, an MCA I analyser 1902, a classifier 1903, an object position determiner 1904, a correlator 1905, a visualisation data generator 1906, a user output driver 1907, a controller 1908, and a storage medium 1909.

[0074] While the sub-modules of control logic comprised in the radiation monitoring control logic 190 are typically described herein as being comprised in the same overall module of hardware and I or software (e.g. as functions implemented in a software package running on a general purpose computer), it will be appreciated separate sub-modules may in other embodiments be distributed between different instances of hardware and / or software control logic. For example, functionality of some sub-modules such as the MCA I analyser 1902 may be implemented in hardware as part of a radiation detector system 100, and functionality of other sub-modules such as classifier 1903, object position determiner 1904, correlator 1905, and visualisation generator 1906, may be implemented using control logic implemented by computing resources situated distant from the pedestrian radiation monitoring apparatus 1. For example, functionality of any of these latter submodules may be implemented using cloud-computing resources, with input and output data transmitted to and received from the cloud-computing resources via the internet or another other package data transfer protocol implemented by the communication interface 1901.

[0075] The communication interface 2901 is configured to send transmit signals to and I or receive signals from a radiation detector system 100 of a radiation monitoring apparatus 1 with which the radiation monitoring control logic 190 is configured for use (such as a gamma radiation detector 100A and neutron radiation detector 100B). Where the radiation monitoring control logic 190 comprises MCA I analyser control logic 1902, the communication interface 1901 is typically configured to receive radiation data in the form of raw sensor output data (e.g. voltage pulses) from the radiation detector(s). Where the MCA I analyser control logic 1902 is integrated into a radiation detector of a radiation detector system 100 (e.g. as part of detector-integrated front-endP131127GB

[0076] signal processing circuitry), or implemented as one or more standalone modules (e.g. standalone front-end signal processing control logic), disposed between a radiation detector and radiation monitoring control logic 190, the communication interface 2901 can be configured to receive part-processed radiation data, for example in the form of detection event count rates for different absolute or relative ranges of energy or frequency.

[0077] In use of the radiation monitoring control logic 190 with pedestrian radiation monitoring apparatus 1, radiation data is recorded by each radiation detector (e.g. gamma radiation detector 100A and neutron radiation detector 100B) of the radiation detector system 100 during each of a plurality of successive time intervals (referred to herein as capture intervals), during a period over which at least one object (e.g. a pedestrian 1021 and I or 1022) travels through a monitoring region 105 of the pedestrian radiation monitoring apparatus 1. The radiation data is transmitted to the radiation monitoring control logic 190 via communication interface 1901. The radiation data may be continuously collected, or the radiation detector system 100 may be triggered by the radiation monitoring control logic 190 to collect radiation data only for time periods over which at least one object of interest (e.g. pedestrians 1021 and I or 1022) is determined to be in a monitoring region 105. Such determination may be made, for example, based on information received by the radiation monitoring control logic 190 from an object positioning system 120 as described further herein. The analyser module 1902 (which may typically comprise MCA control logic, but may in other embodiments operate as a single-channel analyser, SCA) receives the radiation data associated with one or more objects within the monitoring region 105, collected by each radiation detector (e.g. gamma radiation detector 100A and neutron radiation detector 100B) during each of a plurality of capture intervals. For gamma radiation data captured by a gamma radiation detector 100A during each capture interval, the analyser module 2902 may combine the gammaray spectra detected from each gamma radiation detector in order to generate a higher intensity, combined gamma radiation spectrum (the data representing the combined gamma radiation spectrum is referred to as combined gamma radiation data). This allows the captured gamma radiation to be analysed even for a low gamma-ray source intensity. In order to maintain a combined gamma-ray spectrum of good quality for use in the subsequent signal processing stages, each gamma radiation detector 100A may be continuously stabilised and calibrated in order to avoid the impact of changing environmental conditions (e.g. temperature fluctuations). The combining of gamma radiation data from multiple detectors is known in the art (see e.g. [1] and [2]) and is therefore not described in detail here.

[0078] In embodiments where it is included, a user output driver module 1907 can be configured to cause information to be transmitted to a display device 191 (e.g. a monitor for display of image and I or video data comprising visualisation data for display to a user). A data storage medium 1909 (e.g. in the form of a hard disk drive, solid state drive, tape drive or the like) is for storage of any dataP131127GB

[0079] received and I or generated by sub-modules of the radiation monitoring control logic 190. It will be appreciated that, rather than the radiation monitoring control logic 190 comprising the storage medium 1909, the storage medium 1909 may be located in a separate apparatus (e.g. cloudcomputing server or local standalone server) accessible to the radiation monitoring control logic 190 over the internet, a local area network, or the like (e.g. via the communication interface 1901). A classifier module (control logic) 1903 can be provided, being configured to receive radiation data processed by the MCA I analyser module 1902, and identify, for example using spectral analysis approaches known in the art, one or more radiation sources based on the characteristics of the radiation data. For example, where a radiation detector used with the method is a gamma radiation detector 100A as in Figures 1, 2, and 4, the classifier module 2903 can be configured to process data received from the MCA I analyser module 2902 to identify radioisotopes of interest in spectra for one or more capture intervals (or aggregated capture intervals), using approaches known to the skilled person, such as those described in [3] or [4],

[0080] An object position determiner module 1904 is configured to receive object position data generated by an object position sensing system 120, wherein the object position data is indicative of positioning of each of one or more objects within a region from which a radiation detector (e.g. gamma radiation detector 100A and I or neutron radiation detector 100B) is configured to receive radiation, and detect the change in the spatial position of each object a between a first time point and a second subsequent time point based on the object position data. The communication interface 1901 is configured to receive object position data from at least one object position sensing system 120 over a suitable wired or wireless data link, and pass it to the object position determiner module 1904.

[0081] A correlator module 1905 is configured to receive from the object position determiner module 1904 information about a detected change in the spatial position of at least one object within a region from which a radiation detector is configured to receive radiation. The correlator module 1905 is further configured to receive radiation data (e.g. in the form of one or more spectra of radiation intensity with respect to radiation energy or frequency) from the MCA I analyser module 1902, determine a change in a radiation intensity parameter between the first time point and the second subsequent time point, from the radiation data, and correlating the detected change in the spatial position the at least one object with the determined change in the radiation intensity parameter.

[0082] A visualisation data generator module 1906 is configured to generate visualisation data for output to the display 191 (optionally via the user output driver module 1907). The visualisation data generator module 1906 is configured to generate visualisation data in the form of one or more images or video streams, containing representations of each of one or more objects within aP131127GB

[0083] monitoring region 105 from which at least one radiation detector (100A, 100B) of a radiation detector system 100 is configured to receive radiation. The communication interface 1901 is configured to receive image and I or video data from at least one imaging system (which may be an object positioning system 120) over a suitable wired or wireless data link, and pass it to the visualisation data generator module 1906. The visualisation data generator module 1906 may be further configured to determine indications of object types for objects represented in the image and I or video data. As described further herein, the visualisation data generator module 1906 may be configured to assign one or more labels to each of at least one representation of at least one object in the visualisation data, for display to a user in association with the representation of the of at least one object. The labels may indicate information including, but not limited to: a type of object represented in the visualisation data (e.g. an unique identity, or an identity of a class to which the object belongs), a degree of correlation between a change in spatial position of an object represented in the visualisation data and a corresponding change in a radiation intensity parameter, and / or a type of radiation source determined by a classifier module 1903 to be associated with radiation received by at least one radiation detector (100A, 100B) of the radiation detector system 100. The visualisation data generator module 1906 is typically implemented by software control logic configured to use resources of at least one GPU in generating image and I or video data, and label data, together referred to as visualisation data, for output to a user via a display module 191.

[0084] The controller 1909 may be configured to control the operation of each of the other modules of the radiation monitoring control logic 190. The controller 1909 may also control, via the communication interface 2901, the operation of one or more radiation detectors (e.g. gamma radiation detector 100A and neutron radiation detector 100B), and one or more object position sensing systems, as described herein. Each of the sub-modules of the radiation monitoring control logic 190 may be implemented as hardware control logic (such as by one or more ASIC or FPGA modules), and I or as software control logic implemented on one or more general purpose computing devices. It will also be appreciated that sub-sets of the sub-modules 1901 to 1909 shown in Figure 6 may be distributed between different computing devices implementing their functionality via hardware and I or software control logic. Any or all of the sub-modules of the radiation monitoring control logic 190 may be implemented via cloud-computing resources. Figure 7 schematically shows a process flow associated with sub-modules of radiation monitoring control logic 190 shown in Figure 6, according to embodiments of the present disclosure. The exemplary process flow will be explained in the context of a pedestrian radiation monitoring apparatus 1 as shown in Figures 1, 2, and 4, and described further herein. However, it will be appreciated in different contexts aspects of the process flow may be modified to account for different use cases. For example, while position monitoring system 120 may be specifically anP131127GB

[0085] imaging system (in which case an additional imaging system 130 may not be included), it will be appreciated as described herein that other forms of position monitoring system 120 (e.g. a satellite based system making use of the global positioning system (GPS), a light detection and ranging (LiDAR) system, an acoustic ranging system (e.g. an ultrasonic positioning system), and a depth detection system) can be used to provide object position data to an object position determiner module 1904 for determining a change in a spatial position of one or more objects in a monitoring region 105. The process flow may also be modified as described further herein to account for different types of radiation to be monitored, other than the gamma radiation typically used as an example in conjunction with the process flow of Figure 7.

[0086] As shown schematically in Figure 7, and described further herein, the communication interface 1901 is configured to receive radiation data from a radiation detector system 100 of a pedestrian radiation monitoring apparatus 1, and pass the radiation data to a radiation analyser (i.e. MCA) module 1902, for processing of the radiation data into a form comprising, for example, at least one spectrum of radiation intensity with respect to detection energy or frequency. The analyser I MCA module 1902 provides radiation data relating to radiation collected by the radiation detector system 100 over at least a first capture interval relating to a first time, ti , and a second capture interval relating to a subsequent time, t2. The times ti and t2 may be respective start times, midpoint times, or end times, of consecutive capture intervals; or may be respective start times, midpoint times, or end times, of capture intervals separated by an intervening dwell time. Figure 5 shows a visual representation of radiation data which may be generated by the analyser / MCA 1902 based on gamma radiation data received from a gamma radiation detector 100A of a radiation detector system 100 via communication interface 1901. This shows plots of radiation intensity (in counts or count rate) with respect to gamma detection energy associated with each of a first time ti and a second time t2. Characteristic emission peaks 301 and 302, falling within a sub-range Eaof energy, and associated with a particular gamma-emitting radioisotope are schematically indicated.

[0087] The analyser / MCA 1902 passes the radiation data relating to at least times ti and t2 (e.g. the gamma radiation spectra relating to times ti and t2 as shown schematically in Figure 5) to the correlator module 1905 for correlation, by the correlator module 1905, of a detected change in a spatial position of each of one or more objects between times ti and t2, with a change between times ti and t2 in a radiation intensity parameter derived by the correlator module 1905 from the radiation data.

[0088] The analyser I MCA 1902 may also optionally pass the radiation data relating to at least times ti and t2 to a classifier module 1903 for identification of a source material (e.g. radioisotope), and I or source material class (e.g. special nuclear material (SNM), naturally occurring radioactiveP131127GB

[0089] material (NORM), medical radiation source, or industrial radiation source), using spectral analysis approaches known to the skilled person. The identification may be carried out only for radiation data corresponding to the capture interval(s) associated with ti , or both ti and t2, or the span from ti to t2, or radiation data corresponding to a wider time range of capture intervals preceding ti. In the example spectra of Figure 5, classification of a source material may comprise applying a peakfitting routine to identify, based on characteristic emission peaks 301 and 302 (and I or other spectral features), a most likely source material, based on correlating the peaks and I or other spectral features with predefined characteristics of each of a predefined set of source materials. The object position determiner module 1904 is configured to receive object position data from an object position sensing system 120, wherein the object position data is indicative of positioning of each of one or more objects within a monitoring region 105 from which the radiation detector(s) (100A, 100B) of the radiation detector system 100 are configured to receive radiation, and detect a change in the spatial position of each object from times ti to t2 based on the object position data. Figure 1 shows an object position sensing system 120, positioned above the radiation detector system 100. In this example, the object position sensing system 120 is not coincident with either of the gamma radiation detector 100A or the neutron radiation detector 100B, but employs at least one object position sensor distinct from either of the gamma radiation detector 100A or the neutron radiation detector 100B. In this context, ‘distinct’ means that the at least one object position sensor of the object position sensing system 120 generates data which is different from the radiation data generated by either gamma radiation detector 100A or the neutron radiation detector 100B. However, it will be appreciated that in some instances radiation data and object position data may be collected by the same detector or detector system, and in such instances a radiation detector and an object position sensor of an object position sensing system may be considered coincident with one another (i.e. being the same sensor I detector).

[0090] The object position sensing system 120 generates object position data indicative of positioning of each of the one or more objects within the monitoring region 105 (e.g. the positioning of pedestrians 1021 and 1022 in the example of Figures 1, 2, and 4). It will be appreciated herein that what is relevant is that the object position sensing system is configured to detect a change in spatial position(s) of one or more objects within a monitoring region of a radiation detector (i.e. a region from which the radiation detector is configured to receive radiation), and that the change in position(s) of the object(s) can thus be considered to be relative to the position of the radiation detector (i.e. changes in object spatial position(s) can be considered changes in spatial positions within a reference frame fixed to the radiation detector). Thus the concept herein of detecting changes in object position relative to a radiation detector can be applied to scenarios where, in a given reference frame (e.g. an earth-centred reference frame) one or more of the objects do not change spatial position between a first time ti and second time t2, but the radiation detector doesP131127GB

[0091] change spatial position. This may be the case, for example, when the radiation detector is comprised in a mobile radiation monitoring apparatus, as described herein. In any context herein, it will also be appreciated that the object position sensing system may change spatial position between times ti and t2, provided it is able to generate object position data indicative of positioning of each of the one or more objects within the monitoring region 105 of a radiation detector 100A. It will be appreciated if the movement of an object sensing system 120 relative to a radiation detector 100A between times ti and t2 is known, this can be used to register resulting object position data to the radiation detector 100A (i.e. perform a conversion of object positions from a frame of reference fixed on the position sensing system 120 to one fixed on the radiation detector 100A).

[0092] The specific selection of object position sensor / sensors comprised in the object position sensing system 120 will be dependent on a positioning method the object position sensing system 120 is configured to implement. In the example shown in Figures 1, 2, and 4, the object position sensing system 120 is a light detection and ranging (LiDAR) system. As the skilled person is aware, LiDAR systems are commercially available, implementing one or more of: (i) a structured or coded light depth-detection approach, (ii) a depth detection approach based on spatially separated locations of two cameras configured to monitor a shared field of view, and (iii) a time-of-flight based depthdetection approach. Thus in the pedestrian radiation monitoring apparatus 1 of Figures 1, 2, and 4, a LiDAR system (e.g. a commercially available system such as the Realsense™ range of LiDAR position sensing systems manufactured by Intel™) may be provided as object position sensing system 120, being positioned to monitor a spatial region corresponding at least in part to the monitoring region 105. The viewing angles (i.e. expressed as an azimuthal, polar, and I or solid angle) of such a LiDAR system can be configured to substantially match that of one or both of the gamma radiation detector 100A and / or neutron radiation detector 100B. A separate object position sensing system 120 may be provided for each of a plurality of radiation detectors comprised in a radiation detector system 100, particularly where these are configured to detect different forms of radiation, and I or have different sensitivity and I or viewing angles, such that their monitoring regions 105 have different spatial extents.

[0093] As an alternative to a LiDAR object position sensing system 120, or to provide additional object position information, the object position sensing system 120 may comprise a satellite-based location sensing system, an acoustic (e.g. ultrasonic) ranging system, or depth detection system. As described further herein, as an alternative to a LiDAR object position sensing system 120, or to provide additional object information in conjunction with LiDAR object position data, an imaging system 130 may be provided, comprising one or more optical still or video imaging cameras for obtaining scene views of one or more portions of the monitoring region 105. While LiDAR is typically considered an ‘imaging’ approach, because it involves the detection of light from a sceneP131127GB

[0094] of interest, an additional imaging system 130, where provided, is typically configured to provide still image or video data to aid in object detection within the monitoring region 105, and may typically be configured to provide imagery with a higher spatial resolution, and higher dynamic range, than the data generated by a LiDAR object position sensing system 120. However, as described further herein, a non-LiDAR imaging system 130 may also used as an object position sensing system 120, for example where a LiDAR system is not implemented.

[0095] Thus, in the pedestrian radiation monitoring system 1 of Figures 1, 2, and 4, the object position sensing system 120 may comprise an imaging system configured to generate images representing the monitoring region 105. Whether or not the object position sensing system 120 comprises an imaging system, the object position sensing system 120 is configured to generate object position data indicative of spatial positioning of each of one or more objects within the monitoring region. It will be appreciated that this object position data may represent either absolute position data for at least one object for at least two points in time, and I or data indicating relative positions for at least one object for at least two points in time (e.g. in the form of a distance). It will be appreciated that object position sensing systems such as GPS may provide an absolute indication of object position (e.g. in the form of coordinates of each object within the monitoring region 105 at a specific point in time). However, where the object position sensing system 120 is a LiDAR system or other image-based system, the object position data may indicate for at least one object, a distance of the object from a reference position (i.e. coincident with an imaging sensor of the object position sensing system 120), for a given point in time.

[0096] Thus an image-based object position sensing system 120 such as a LiDAR system may be configured to generate object position data in the form of an image sequence comprising at least a first image of each of at least one objects in the monitoring region 105 at a first time point and a second image of each at least one object at the second time point. Optionally, such an image sequence may comprise a plurality of further images generated by the object position sensing system 120 at sequential time points between the first time point and the second time point. Such a sequence of time-separated images may be termed object position video data. The object position data may be continuously acquired during operation of the pedestrian radiation monitoring apparatus 1, and transmitted from the object position sensing system 120 to the communication interface 1901 of the radiation monitoring control logic 190, or acquisition of object position data may be triggered by detection of a change in a characteristic of radiation detected by one or more radiation detector(s) of the radiation detector system 100. For example, if a gamma or neutron radiation count rate determined by analyser / MCA 1902 exceeds a predefined threshold indicating likely presence of a radiation source in the monitoring region 105, the radiation monitoring control logic 190 may trigger the object position sensing system 120 to start obtaining object position data sequential time points, and at least at a first time ti , and subsequentP131127GB

[0097] time t2, until the gamma or neutron radiation count rate determined by analyser I MCA 1902 to have exceeded the threshold returns once again to a level below the threshold.

[0098] As shown schematically in Figure 7, the object position data generated by the object position sensing system 120 is transmitted to the object position determiner module 1904 of the radiation monitoring control logic 190 via the communication interface 1901. The object position determiner module 1904 is configured to analyse the object position data to detect a change, between a first time point ti and a second, subsequent time point t2, in a spatial position of one or more objects within the monitoring region.

[0099] Figures 8 and 9 show schematically aspects of a position detection routine applied to object position data by the object position determiner module 1904 according to aspects of the present disclosure. Figure 8 shows a virtual representation 105’ of a monitoring region 105 containing respective representations 102T and 1022’ of two objects comprising a first pedestrian 1021 and 1022. It will be appreciated the virtual representation 105’ of the monitoring region corresponds to a scene viewed from an imaging system comprised in the object position sensing system 120 shown in Figures 1, 2, and 4. The representations of pedestrians 102T (ti) and 1022’ (ti) are associated with the spatial configuration of the pedestrians 1021 and 1022 relative to the object position sensing system 120 at time ti (i.e. the configuration shown schematically in Figure 2), and the representations of pedestrians 102T (t2) and 1022’ (t2) are associated with the spatial configuration of the pedestrians 1021 and 1022 relative to the object position sensing system 120 at subsequent time t2 (i.e. the configuration shown schematically in Figure 4). Thus Figure 8 shows schematically overlaid representations of each of pedestrians 1021 and 1022 in the monitoring region 105 of the pedestrian radiation monitoring apparatus 1, at each of times ti and t2. In this example, representations 102T (ti) and 1022’ (ti) correspond to representations of pedestrians 1021 and 1022 in a first LiDAR image acquired by object position sensing system 120 at a first time ti , and representations 102T (t2) and 1022’ (t2) correspond to representations of the same pedestrians 1021 and 1022 in a subsequent LiDAR image obtained by the same object position sensing system 120 at subsequent time t2. As is known to the skilled person, it is typical for pixel intensity in LiDAR images to be scaled such that the pixel intensity (i.e. greyscale value) is proportional to linear distance from the imaging location to an object at the location in the image scene corresponding to the pixel location. Thus, a change in a distance of pedestrian 1021 from the location of the object position determiner module 120 over the time period from ti to t2 can be detected by the object position determiner 1904 by evaluating a distance from the object position determiner module 120 associated with each of representation 102T (ti) and representation 102T (t2), and calculating the difference between these distances. The distance of a given representation from the object position determiner module 120 at a given point in time can be evaluated, for example, by detecting an outline of the representation in the correspondingP131127GB

[0100] LiDAR image, or an outline of a sub-feature of the representation (e.g. a head, hand, torso, or other feature), and averaging the pixel intensity value for the enclosed pixels to return an average distance. Identification of pixels belonging to the representations of the same physical object in different images can be achieved using different 2D or 3D object tracking approaches known in the art, such as digital image correlation (DIG) or digital volume correlation (DVC) approaches, and I or approaches using trained neural networks (e.g. a trained convolutional neural network) to track shapes or textures across time through a plurality of input images. Such approaches are well known in the art and are not explained in detail here.

[0101] Once the difference in scalar distance from each pedestrian (1021, 1022) to the object position sensing system 120, over the period from ti to t2, has been computed, then based on predefined quantification of the relative positions of the object position sensing system 120 and the gamma radiation detector 100A, the object position determiner module 1904 can determine using simple trigonometric functions the change in scalar distance between each of pedestrians 1021 and 1022 and the gamma radiation detector 100A over the same period. In other scenarios, the machine learning model may be trained to directly output, based on an input of LiDAR image data, a change in distance between each pedestrian (1021, 1022) and the gamma radiation detector 100A, based on the change in position within the scene 105’ of the representations (1021’, 1022’) of the pedestrians, over the period from ti to t2. As discussed further herein, it will be appreciated that the change in distance from the object(s) (e.g. pedestrians) to the radiation detector 100A may be due to movement in the same reference frame, between times ti and t2, of both the radiation detector 100A and the object(s), movement of the radiation detector 100A relative to one or more fixed objects, or movement of one or more objects relative to a fixed radiation detector 100A.

[0102] Image data which does not directly provide a representation of distance from an imaging position to representations of objects in the imaged scene (i.e. non-LiDAR images) may also be used to determine a change in position, using image correlation approaches. As known to the skilled person, a trained machine learning model, such as a Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Autoencoder (AE), or Generative Adversarial Network (GAN), can be applied for monocular depth estimation (i.e. depth estimation for representations of objects in standalone images obtained from a single imaging location). Open-source models known to the skilled-person such as MiDAS, ZoeDepth, PatchFusion and Marigold, for example, can be implemented by the object position determiner module 1904, configured to receive a first image of the monitoring region 105, acquired by an optical imaging sensor of an object position sensing system at a time ti , and process the image to provide an output image scaled such that the pixel intensity (e.g. greyscale value) is proportional to linear distance from the imaging location to an object at the location in the image scene corresponding to the pixel location. The same processP131127GB

[0103] can be applied to a second image of the monitoring region 105, acquired by the optical imaging sensor of the object position sensing system at a subsequent time t2. The resulting processed images, for each of times ti and t2, can be analysed as described further herein for LiDAR images, to detect a change in spatial position (e.g. a change in distance) of each of at least one objects represented in the image data.

[0104] Other means of tracking representations of objects in object position data comprising image I video data may be implemented by the object position determiner module 1904. Figure 9 will be recognised from Figure 8, and shows schematically overlaid representations of each of pedestrians 1021 and 1022 in the monitoring region 105 of the pedestrian radiation monitoring apparatus 1, at each of times ti and t2. In this example, representations 102T (ti) and 1022’ (ti) correspond to representations of pedestrians 1021 and 1022 in optical camera images acquired by an imaging sensor of an object position sensing system 120 at a first time ti, and representations 102T (t2) and 1022’ (t2) correspond to representations of the same pedestrians 1021 and 1022 in a subsequent optical camera image obtained by the same object position sensing system 120 at subsequent time t2. The images obtained at each of times ti and t2 may be frames from a video stream, or still images. As known to the skilled person, a trained machine learning model can be implemented by the object position determiner module 1904, being applied to images of a scene (such as scene 105’ shown in Figure 9) to identify each of one or more objects represented in the scene, and track their position within the scene between different time points (i.e. between each of two time points ti and t2). For example, a CNN, RNN, AE, or GAN, may be trained based on images and I or videos of objects (such as images containing representations of pedestrians 102T and 1022’ in a scene 105’ as shown in Figure 9), generated by an image sensor of an object position sensing system 120, wherein the images and I or videos are labelled with spatial position information related to each object. For example, objects represented in images and I or videos (known as training data) may be labelled with a scalar distance d from the object position sensing system 120, such that the trained machine learning model is configured to output estimated distances of each of a plurality of represented objects from an object position sensing system 120, based on an input of image and I or video data, generated by the object position sensing system 120, containing representations of said objects. Open-source object tracking models known to the skilled-person, such as OpenCV, DeepSORT, or MDNet, for example, can be implemented by the object position determiner module 1904 for object tracking in image sequences (i.e. video data or pairs of still images). As shown in Figure 9, the output of a machine learning model applied by the object position determiner module 1904 to track representations 102T and 1022’ of pedestrians 1021 and 1022 respectively in time-separated images of a monitoring region (i.e. in scene 105’), may be expressed in the form of vectors indicating change of spatial position of the pedestrians 1021 and 1022 within the monitoring region 105. Thus between times ti and t2, the representation 102T of pedestrian 1021P131127GB

[0105] is determined to have moved through vector V1021, and the representation 1022’ of pedestrian 1022 is determined to have moved through vector V1022. Based on predefined quantification of the relative positions of the object position sensing system 120 and the gamma radiation detector 100A, the object position determiner module 1904 can determine using simple trigonometric functions the change in scalar distance between each of pedestrians 1021 and 1022 and a reference position on the gamma radiation detector 100A over the time period between ti and t2. In other scenarios, the machine learning model may be trained to directly output, based on an input of image I video data, a change in distance between each pedestrian (1021, 1022) and the gamma radiation detector 100A, based on the change in position within the scene 105’ of the representations (102T, 1022’) of the pedestrians, over the period from ti to t2.

[0106] It will be appreciated that the machine learning approaches described herein for determining a change in spatial position of each of one or more objects, based on image I video data comprising representations of the object(s), will typically be configured to uniquely identify each object in the scene, for the purpose of tracking each object across each of two or more sequential time points. However, in some embodiments of the present disclosure, either of the object position determiner module 1904 or visualisation data generator module 1906 described herein may be further configured to process an image sequence by applying a second trained classifier, preferably a neural network, to the image sequence, and outputting from the second trained classifier an indication of an object type associated with each of the one or more objects. The image sequence may comprise image data (e.g. LiDAR or other camera data) used for spatial position change detection as described further herein, or may comprise complementary image data of the monitoring region (e.g. the image data may comprise video data of the monitoring region 105, obtained by a video camera comprised in an object position sensing system 120, or imaging system 130. At each of one or more time points at which at least one object in the monitoring region 105 of a pedestrian radiation monitoring apparatus 1 is imaged, or otherwise detected by the object position sensing system 120 to facilitate detection of a change in spatial position, an image (e.g. a video frame) corresponding to said time point(s) may be input to a trained machine learning model to identify an object type associated with the at least one object. Any objectrecognition model known to the skilled person may be implemented in the radiation monitoring control logic 190 for identification of object type, including but not limited to YOLOvIO, EfficientDet, RetinaNet, Faster R-CNN, or DETR (Detection Transformer). The model may be trained based on images and I or videos of objects (such as images containing representations of pedestrians 102T and 1022’ in a scene 105’ as shown in Figure 9), generated by an image sensor of an object position sensing system 120, wherein the images and I or videos are labelled with an object type. Object types may be defined at different levels of generality, such that: a general class ‘person’ may be defined along with sub-classes ‘adult’, ‘child’, ‘male’, female’ etc; and a general class ‘vehicle’ may be defined along with sub-class ‘car’, ‘truck’, ‘motorcycle’,P131127GB

[0107] ‘bicycle’, etc. Other general classes such as ‘animal’ and ‘baggage’ may also be defined, with their own sub-classes, according to particular operating requirements for a specific use context. The radiation monitoring control logic 190 is thus configured to detect a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within a region from which a radiation detector is configured to receive radiation (e.g. in terms of change in distance between each object and the location of the radiation detector), and furthermore may be configured to generate a label associated with each of one or more objects in an image of the region, obtained at one or more of the first and second time points, wherein the label comprises an indication of object type. As discussed further herein, the object position data and optionally the label(s), for each of a plurality of time points, can be stored in the storage medium 1909 until required for further processing by other modules of the radiation monitoring control logic 190, and I or for display on the display unit 191.

[0108] The radiation monitoring control logic 190 is further configured to determine, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of an intensity of radiation detected by the radiation detector; and correlate the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter. Thus, as shown schematically in Figure 6, a correlator module 1905 can be provided in radiation monitoring control logic 190 to carry out said correlation. As shown schematically in the process flow of Figure 7, the correlator module 1905 is configured to take as inputs

[0109] i. data indicating a change of position of each of one or more objects between a first time point ti , and a subsequent time point t2, generated by an object position determiner module 1904 according to approaches set out further herein, and

[0110] ii. data indicating a change in an intensity of radiation detected by a radiation detector (e.g.

[0111] gamma radiation detector 100A), between the first time point ti , and the subsequent time point t2, generated by radiation analyser module 1902 according to approaches set out further herein.

[0112] The correlator module 1905 comprises control logic configured to correlate the indication of the change in position of each of the one or more objects, with the change in intensity of radiation, over the time period from ti to t2. A change in intensity of radiation, / , measured at the radiation detector (e.g. gamma radiation detector 100A), can be quantified according to any approach known to the skilled person. Thus, as described herein, the radiation intensity parameter / , may be quantified by, for example, numerically integrating under a spectrum of gamma radiation intensity (i.e. counts), based on radiation data from the gamma radiation detector 100A, for eachP131127GB

[0113] of times ti and t2. Thus, with respect to the exemplary gamma radiation spectra associated with times ti and t2, schematically shown in Figure 5, the radiation intensity profiles at the respective time points ti and t2 can be represented as:

[0114]

[0115] where ftE) represents the relationship between count rate (r) and gamma radiation detection energy (E) at a given time t. A measure of radiation intensity ( / ) for each time point can then be represented as:

[0116] hi = fE1fti dE,

[0117] and,

[0118] It2= fE1ft2(E dE,

[0119] where E1 and E2 are endpoints of a range of detection energy, which can be the entire detection range of the radiation detector, or a sub-range as described further herein.

[0120] For each of one or more objects within the monitoring region 105 of the radiation detector, the correlator module 1905 may, in embodiments, receive from the object position determiner module 1904 an indication of a distance between the object and the radiation detector at time ti (i.e. du) and at time t2 (i.e. dt2). For a given object, if the object comprises a radiation source responsible for the change in radiation intensity observed at the detector (i.e. It2- / tl), then an inverse square law assumption for radiation propagation through 3D space means that the following relationships will be at least partially satisfied:

[0121]

[0122] such that

[0123] Ci=hi dtl, and C2=2dt2,P131127GB

[0124] where C is the radiation intensity at the source.

[0125] Assuming the radiation source has constant intensity (i.e. 67=62), then the following equation would, in an idealised scenario, be satisfied:

[0126] ki d-ti = It2 dt2

[0127] In embodiments of the present disclosure, the skilled person may modify this equation to account for one or more potential sources of uncertainty. These may include, the following:

[0128] • a first set of uncertainties U(dt) may be associated with the position of the radiation source on or within a given object whose change of spatial position (i.e. change in d) is detected. It will be appreciated that values of dti and dt2 for a given object may, as non-limiting examples, be based on a reference point associated with the object (e.g. a centroid of a determined shape of a representation of the object), or based on an average distance evaluated based on distances associated with a plurality of points defined on the object. In either case, the values of dti and dt2 are unlikely to correspond exactly to the location of a radiation source within the object. For example, where the object is a pedestrian, values of dti and dt2 evaluated based on an average distance of a surface of the pedestrian’s entire body, based on data from a LiDAR sensor of an object position sensing system 120, will likely be either an under- or over-estimate of the true values for a source located in the pedestrian’s hand. This type of uncertainty (i.e. U(df)) may be reduced by sub-dividing a given object into a plurality of sub-regions, and correlating change in position to change in radiation intensity parameter, for each sub-region. The correlation value (o), for a given object may be taken as the highest correlation value from among a plurality of correlation values where each is associated with a different one of a plurality of sub-regions defined for the object.

[0129] • a second set of uncertainties U1(!i) may be associated with shielding of a radiation source on or within a given object when the object passes behind a shielding object within the scene. Where at ti and / or t2 a second object is disposed partially or fully between the radiation detector position and a the position of a first object for which change of spatial position and change of radiation intensity parameter is being correlated, a degree of shielding can be estimated for the second object, and used to add a scaling factor to either of / tland I or It2. For example, using object recognition approaches described herein, a potentially shielding object may be identified (e.g. as a human, an animal, a vehicle, etc), and a degree of shielding provided by said object may be estimated based on previous simulations and / or empirical quantification. Thus a value of ltor a given object underP131127GB

[0130] assessment can be scaled to account for an estimated degree of shielding of the object under assessment at the radiation detector location by an identified shielding object. • a third set of uncertainties U2(lt) may be associated with a dependence of the intensity measured at the radiation detector on an angle between the radiation detector and a given object. In other words, for a given radiation-emitting object, given a constant source activity and constant distance from the detector, the radiation intensity measured at the detector (e.g. in terms of a count rate of detection events) may not be constant with respect to the angle of the object to the detector, but may instead have an angular dependency. As the skilled person is aware, such angular dependency can be quantified for a given detector, and this can be used as a scaling factor for a value of lt, with the angle determined based on object position data obtained by the object position sensing system 120.

[0131] It will also be appreciated that a solid angle subtended at the detector by an object can be used to scale the intensity value lt, particularly where the object is close to the radiation detector (i.e. where the distance d of the object to the radiation detector is within an order or magnitude of the detector width). The solid angle subtended by an object for a given radiation detector geometry and distance from the radiation detector can be estimated, or determined by finite element modelling, for example, and experimentation or modelling used to determine an appropriate scaling factor between the solid angle and the intensity value lt.

[0132] Figure 10A shows schematically an approach to determination of a solid angle, for use in scaling a radiation intensity parameter (i.e. It) according to approaches set out herein. This may be particularly useful in situations where an object, for which a correlation between change of spatial position and change in radiation intensity parameter is being correlated, is close to the radiation detector from which data is used to determine the change in radiation intensity parameter (e.g. the object is at a distance which is within an order of magnitude of a width I diameter of the radiation detector). Figure 10A shows a gamma radiation detector 100A, in plan view, and corresponds to a detail view of the pedestrian radiation monitoring apparatus 1 shown in Figures 1, 2, and 4. At a time t, an object 1021 (here a pedestrian) is at a distance of dt,io2i from the radiation detector 100A, at an azimuthal angle 9 (i.e. an angle around an axis - y- vertical to a ground plane), from a suitable reference (here a front plane of the radiation detector 100A). As evaluated from the location of the object 1021, the radiation detector 100A subtends a solid angle of Q0,t. Because the geometry of the radiation detector 100A is known, he value of Qo,tfor given values of dt,io2i and 9 can be computed based on trigonometric approaches known to the skilled person, and used to scale the radiation intensity parameter (lt) for the object when determining a correlation parameter (e.g. the radiation intensity parameter may be scaled - in a two-dimensional example - by a coefficient computed as Qo.t / n). This concept can be extended to three-dimensions.P131127GB

[0133] Figures 10B and 10C show schematically an approach which may be useful in estimating a degree of shielding of an object in a monitoring region of a radiation detector, and which may therefore be used in mitigating the second set of uncertainties described herein (i.e. uncertainties U1 (It) associated with shielding of a radiation source on or within a given object when the object passes behind a shielding object). Figure 10B shows a gamma radiation detector 100A, in plan view, and again corresponds to a detail view of the pedestrian radiation monitoring apparatus 1 shown in Figures 1, 2, and 4. An object 1023 (here a vehicle) is shown at a first time point ti, positioned relative to the gamma radiation detector 100A, such that in the xz plane, a first solid angle of Qd.ti.u is subtended by the object 1023 with respect to a reference location on or in the gamma radiation detector 100A. The suffix ‘II’ indicates that the solid angle is an unshielded solid angle, meaning it is the solid angle subtended by portions of the object 1023 which are not shielded at the reference location by any intervening object. It will be appreciated that in Figure 10B, the total solid angle subtended by the object 1023 is unshielded. However, at a second, subsequent time t2, a shielding object 200 is interposed between the object 1023 and the gamma radiation detector 100A, such that at t2, the total solid angle subtended by the object 1023 is comprises a first unshielded component Qd,t2,u, and a second, shielded component Qd,t2,s, over which a solid angle subtended at the evaluation location by the shielding object 200 overlaps the total solid angle subtended by the object 1023 (i.e. overlaps the solid angle Qd.ti.u shown in Figure 10B, which is also the total solid angle for object 1023 at ti ) .

[0134] The unshielded solid angle (Qd,t,u) subtended at a location in or on a radiation detector at a time t may be determined based on image data obtained at time t by an object position detection system 120, and I or imaging system 130. An image comprised in such image data may be transformed by a mapping which approximates the field of view of the radiation detector 100A (i.e. such that an equal area of an image of the monitoring region corresponds to an equal solid angle of the monitoring region as viewed from the radiation detector 100A). The unshielded solid angle Qd,t2,u subtended by an object at a time t2, can be determined, for example, by detecting an outline of a representation of the object in the transformed image, and determining the enclosed area of the representation (e.g. in pixels). A shielded solid angle (Qd,t2,s) subtended at the gamma radiation detector 100A by the object att2 may be determined, for example, based on determining a change in unshielded solid angle (Qd,t2,u) since an earlier time ti, when the object is assumed (or determined, for example, on the basis of applying a shape detection approach to the object, and matching the shape to a predefined unshielded shape geometry) not to be shielded by an intervening object. The shielded solid angle Qt2,s at t2 may, in embodiments, be given by:

[0135] d,t2,S=d,tl,U ~ d,t2,U

[0136] In embodiments of the present disclosure, tracking of Qt,u and Qt,s by the radiation monitoring control logic, for a given object at different values of t, for example using image data obtained byP131127GB

[0137] the object position sensing system 120 and / or imaging system 130, can be used by the correlator to implement optional refinements, including the following:

[0138] • in embodiments, a radiation intensity parameter (lt) for a given object at a time t may be scaled by the correlator module, by a coefficient which compensates for a degree of shielding of the object at that point in time, as represented, for example, by the ratio of the unshielded solid angle of the object to the total solid angle of the object. The skilled person can determine using modelling or empirical methods a suitable form of scaling factor, but this may generally take the form:

[0139] &

[0140]

[0141] • in embodiments, detection by the correlator module (or, for example, the object position detector module) of a change in the unshielded solid angle subtended by an object between ti and t2 (i.e. a non-zero value of | / 2t2,u - ^ti.u |) may be used to determine that the object is being shielded by at least one further object, and that a scaling factor to compensate for shielding should be applied to the correlation. The scaling factor may be a coefficient based on a function of flt uand flt sas, and I or may be computed based on identification of the shielding object type (e.g. using a trained machine learning algorithm as described here) and determination of a predefined degree of shielding associated with said type of object, as described further herein.

[0142] A correlation parameter (o) can be computed by the correlator module for each of one or more objects having a detected change in spatial position between at least a first time point ti and a subsequent time point t2, for which corresponding radiation intensity data (i.e. radiation intensity parameter data) has been obtained, where:

[0143]

[0144] The correlation parameter represents the likelihood that a given object is an emitter of radiation detected by the radiation detector, for an energy or frequency range over which a radiation intensity parameter has changed between times ti and t2, based on its change in spatial position over the same period of time. It will be appreciated that either of Itldtl2and I or It2dt22in the above correlation parameter expression may be modified by using scaling parameters to reduce uncertainty, using approaches set out herein. Thus, by being configured to compute a correlation parameter for each of at least one or more objects in a monitoring region 105, the correlator module 1905 can classify none, at least one, or a plurality of the objects as in a monitoring region 105 as an emitter of radiation detected by a radiation detector, based on a degree of correlation between a detected change in spatial position of each object and a determined change in aP131127GB

[0145] radiation intensity parameter associated with radiation detected by the radiation detector. The correlation parameter o for a given object, at a time point t2, can be directly used as a measure of likelihood that the object is an emitter of radiation at the time point t2. A determination that an object is an emitter of radiation may be made based on comparing the correlation parameter to a predefined threshold. It will be appreciated that an outcome of this process may be the determination that a single object from among a plurality of objects is an emitter of radiation (i.e. the object has an above-threshold correlation parameter), or that more than one of said plurality of objects is an emitter of radiation, or than none of the plurality of objects is an emitter of radiation. As previously indicated, the radiation intensity parameter ( / ) for each of the time points ti and t2 can be evaluated based on an entire detection energy range of the radiation detector (e.g. gamma radiation detector 100A, neutron radiation detector 100B, or another radiation detector type as described herein). Alternatively, the radiation intensity parameter can be evaluated based on a sub-range of energy, which in embodiments of the present disclosure may be associated with spectral features correlated with a particular type of radiation source (e.g. a particular type of radiation emitting material or device). Figure 11 shows schematically exemplary gamma radiation spectra associated with each of a first time ti and a second time t2, obtained by analyser / MCA module 1902 from the output of gamma radiation detector 100A, according to approaches described in conjunction with Figure 3. Figure 11 shows schematically changes in radiation intensity (i.e. count rate) in first and second ranges of energy Eb and Ec, which respectively enclose first and second characteristic emission peaks 401 and 402, respectively associated with first and second gamma-emitting radioisotopes. It is observed that between times ti and t2, the intensity in the first energy sub-range Eb (as evaluated, for example, by integrating under each spectrum over the sub-range) increases, whereas the intensity in the second energy sub-range Ecdecreases. By correlating the detected change in the spatial position of each of the one or more objects with a determined change in the second radiation intensity parameter for each of a plurality of sub-ranges of detection energy (or frequency) in this manner, the correlator module 1905 can determine for each object a plurality of correlation values, where each correlation value can be considered a measure of likelihood that the object is an emitter of radiation corresponding to the specific sub-range of detection energy (or frequency) at the time point t2. Thus, if the schematic spectra of Figure 11 are considered to relate to the configurations of pedestrians 1021 and 1022 shown in Figure 4, at each of times ti and t2, partitioning the spectra of Figure 11 into a sub-range Eb enclosing an emission peak 401 characteristic of a radioisotope b, and a sub-range Ecenclosing an emission peak 402 characteristic of a radioisotope c, allows the relationships between the pedestrians and the radioisotopes b and c to be discriminated. Over the period from ti to t2, the pedestrian 1021 moves towards to the gamma radiation detector 100A (by a distance dt2-ti,io2i). whereas pedestrian 1022 moves away from the gamma radiation detector 100B (byP131127GB

[0146] a distance dt2-ti,io22)- Accordingly, the correlation between the change in position of pedestrian 1021 and the increased radiation intensity in the energy range Eb will be higher than that for pedestrian 1022, and the correlation between the change in position of pedestrian 1022 and the decreased radiation intensity in the energy range Ecwill be higher than that for pedestrian 1021. On this basis, the correlator module 1905 may be configured to determine pedestrian 1021 as being associated with radioisotope b, and pedestrian 1022 as being associated with radioisotope c. This can be considered a form of classification, whereby the selection of one or more specific sub-ranges of energy (or frequency) over which to correlate change in spatial position of an object with change in radiation intensity parameter, where the sub-range is selected to enclose one or more spectral features having a predefined relationship with a specific type of radiation source, allows the object to be associated not only with a change in radiation intensity, but allows a likely type of radiation source associated with the object to be estimated.

[0147] Thus, in any of the methods described herein, the first radiation intensity parameter may be a radiation intensity parameter indicative of a change in an intensity, between a first time point and second subsequent time point, of radiation detected by a radiation detector and associated with a first sub-range of detection energy from within an overall range of detection energy of the radiation detector, wherein the method further comprises: determining, based on radiation data obtained from the radiation detector, a change in a second radiation intensity parameter between the first time point and the second time point, wherein the second radiation intensity parameter is indicative of a change in an intensity of radiation detected by the radiation detector for a second sub-range of detection energy from within the overall range of detection energy of the radiation detector, the second sub-range being different to the first sub-range; and correlating the detected change in the spatial position of each of the one or more objects with the determined change in the second radiation intensity parameter.

[0148] Correlation values, determined for each of a plurality of time points (e.g. for at least the second time point t2), for each of one or more objects for which a change in spatial position has been determined, and optionally for each of one or more sub-ranges of detection energy, can be stored by the correlator module 1905 in the storage medium 1909 until required for further processing by other modules of the radiation monitoring control logic 190, and I or for display on the display unit 191.

[0149] Further and I or alternative classification of the radiation detected by a radiation detector (e.g. gamma radiation detector 100A) may be carried out by classifier module 1903, according to techniques discussed further herein, and known to the skilled person. Thus, for example, as shown in Figure 7, a classifier module 1903 may be configured to receive spectral data from the analyser / MCA module 1902, and identify at least one source material (e.g. specific radioisotope),P131127GB

[0150] and I or source material class (e.g. special nuclear material (SNM), naturally occurring radioactive material (NORM), medical radiation source, or industrial radiation source), using spectral analysis approaches known to the skilled person (e.g. using peak-fitting approaches, template matching, or any other approach, such as described, for example, in [3] and [4]). Alternatively or additionally, at least one radiation emitting device (e.g. X-ray generator) may be identified based on spectral analysis. The classifier module 1903 may use one or more machine learning approaches (e.g. one or more trained neural networks) to determine one or more types of radiation source responsible for emission of radiation detected by the radiation detector system 100. Thus for at least one of times ti and t2, the classifier module 1903 may determine one or more types of radiation source from radiation data relating to said time(s), pass this information to the visualisation data generator module 1906 of the radiation monitoring control logic 190, and I or store this as label information in the storage medium 1909 until required for further processing by other modules of the radiation monitoring control logic 190, and I or for display on the display unit 191. As described further herein, data from the classifier module 1903 may also be passed to the correlator module 1905 so that a change in radiation intensity parameter associated with one or more specific sources of radiation identified by the classifier module 1903 (e.g. a radiation intensity evaluated over one or more sub-ranges of energy associated with a specific identified radioisotope) can be correlated with a change in spatial position of one or more objects within a monitoring region of the radiation detector.

[0151] Thus, the storage module 1909 may be used to store the following data, for retrieval and further processing by modules including the visualisation data generator module 1906, and I or transmission to external devices, such as, for example a cloud-computing database:

[0152] • Image data obtained by an imaging system 130, showing a view of at least one object in a monitoring region 105 of a radiation detector system 100 at one or more points in time, including at least one of a first time point ti and a second time point t2, and preferably a sequence of images in the form of still images or video frames showing a plurality of further time points.

[0153] • Radiation data obtained by a radiation detector system 100 and processed by a radiation analyser 1902 (i.e. in the form of radiation spectra), associated with at least the first time point ti , and the second time point t2, and preferably the plurality of further time points.

[0154] • Object label data comprising labels indicating a type of object for each of the one or more objects in the image data at one or more points in time, including at least one of the first time point ti and the second time point t2, and preferably the sequence of images in the form of still images or video frames showing the plurality of further time points.

[0155] • Correlation label data comprising a correlation value determined for each of one or more objects, indicating a degree of correlation between a change in spatial location of eachP131127GB

[0156] object between first time point ti and the second time point t2, and a change in radiation intensity determined from the radiation data, for at least one range of detection energy or frequency, where each at least one range of detection energy or frequency optionally has a predefined association with a specific type of radiation source.

[0157] • Source label data comprising at least one label indicating a type radiation source determined to be associated with each of one or more objects in the image data at one or more points in time, including at least one of the first time point ti and the second time point t2, and preferably the sequence of images in the form of still images or video frames showing the plurality of further time points.

[0158] Any of these forms of data may be transmitted direct from their arising module of control logic, in substantially real time, to the visualisation data generator module 1906 of the radiation monitoring control logic 190, or retrieved by the visualisation data generator module 1906 from storage medium 1909.

[0159] It will be appreciated that determination of a degree of correlation between a change in spatial location of each object between first time point ti and the second time point t2, and a change in radiation intensity determined from the radiation data, and determination of object labels, correlation labels, and source labels, may be computed for one a one-off basis, or may be computed on a cyclic I repeating basis. Thus, for example, at a given clock speed of controller 1908 of radiation monitoring control logic 190, these computations may be carried out by setting a current time as the value of t2, and determining the value of previous time ti by subtracting a predefined offset time from the value of t2, where for example, the offset time may be less than 0.001s, less than 0.01s, less than 0.1s, less than 0.2s, less than 0.5s, less than 1s, less than 2s, less than 3s, less than 4s, or less than 5s. Selecting shorter offset times increases the temporal resolution of the radiation monitoring, while typically reducing the accuracy of the correlation between changes in spatial location of objects and resulting changes in radiation intensity determined from the radiation data. Selecting longer offset times reduces the temporal resolution of radiation monitoring, while typically increasing the accuracy of the correlation between changes in spatial location of objects and resulting changes in radiation intensity determined from the radiation data. The skilled person can select an appropriate trade-off between temporal resolution and correlation accuracy depending on a particular use case. Given the accuracy of determination of correlation parameters will be dependent to a degree on the measured intensity of radiation (e.g. lower intensity includes a higher proportion of noise, leading to lower accuracy of correlation), the radiation monitoring control logic 190 may be configured to compensate for changing radiation intensity by automatically varying the offset time between ti and t2to target a constant accuracy in correlation parameter calculation. This can be achieved by determining, via simulation or empirical approaches, a relationship between the accuracy of correlation and theP131127GB

[0160] measured radiation intensity, with respect to offset time, and using this relationship to derive a suitable offset time, given a measured radiation intensity at ti.

[0161] The visualisation data generator module 1906 is configured to generate visualisation data comprising an image or video containing representations of each of one or more objects in the monitoring region 105 of the pedestrian radiation monitoring apparatus 1, and assign at least a one label to a representation of at least one object in the visualisation data, and output the generated visualisation data with the first label to a display unit 191 for display to a user. The at least one label may comprise an object label (i.e. from the object label data) indicating a determined object type associated with the at least one object, and I or may comprise a correlation label (i.e. from the correlation label data) indicating a correlation value associated with the at least one object; and I or may comprise a source type label (i.e. from the source label data) indicating a type of radiation source determined as having an association with the at least one object. Figure 12 shows schematically a visualisation of an exemplary scene 105’ at a point in time t2, as generated by a visualisation data generator module 1906 of radiation monitoring control logic 190. The exemplary scene 105’ may be generated in the following manner. The visualisation data generator module 1906 obtains directly from imaging system 130 and I or object position sensing system 120, or from data storage 1909, image data associated with the time point t2. This may be a still image (e.g. a LiDAR or optical camera image), or a frame of a video. The image contains representations of various objects within a monitoring region 105 of at least one radiation detector (e.g. a gamma radiation detector 100A) of pedestrian radiation detection apparatus 1. Thus in the exemplary scene 105’ of Figure 12, representations 1021’, 1022’, and 1023’, are of human pedestrians, and representation 1024’ is of a dog, all within the monitoring region 105.

[0162] The visualisation data generator module 1906 further obtains (e.g. from data storage 1909) a label indicating a type of object for each of representations 1021’, 1022’, 1023’, and 1024’, and associates each object with its respective label. Thus representation 1021’ is assigned the label 1021A indicating the type as ‘Person’, and in this instance further uniquely assigning a numerical identifier T; representation 1022’ is assigned the label 1022A indicating the type as ‘Person’, and in this instance further uniquely assigning a numerical identifier ‘2’; representation 1023’ is assigned the label 1023A indicating the type as ‘Person’, and in this instance further uniquely assigning a numerical identifier ‘3’; representation 1024’ is assigned the label 1024A indicating the type as ‘Dog’, and in this instance further uniquely assigning a numerical identifier T.

[0163] The visualisation data generator module 1906 further obtains a label indicating, for each representation, a degree of correlation between a change in spatial location of the associated object and a change in radiation intensity parameter, over the period of time between t2 and a preceding time point ti. Thus representation 1021’ is assigned the label 1021 B indicating a degreeP131127GB

[0164] of correlation (i.e. correlation parameter) for the associated pedestrian of 0.9, noting that the correlation parameter is associated with at least one predefined sub-range of energy (Ea) associated with one or more gamma radiation emission peaks characteristic of the radioisotope Barium 133 (Ba-133); representation 1022’ is assigned the label 1022B indicating a correlation parameter for the associated pedestrian of 0.8, noting that the correlation parameter is associated with at least one predefined sub-range of energy (Ec) associated with one or more gamma radiation emission peaks characteristic of the radioisotope Caesium 137 (Cs-137). In this example, the correlation value is computed for each object for Eb and Ec, and the highest resulting correlation value of the two (i.e. the maximum correlation parameter) is the one indicated via the correlation degree label. Representations 1023’ and 1024’ are respectively assigned the labels 1023B and 1024B indicating respective maximum correlation parameters for the associated objects of 0.2 and 0.1.

[0165] The visualisation data generator module 1906 further obtains a label indicating, for at least one representation, a most likely radiation source associated with the change in radiation intensity parameter correlated with the spatial location change for the associated object. In the example of Figure 12, the visualisation data generator module 1906 is configured to assign such a label (i.e. radiation source label) if the maximum correlation parameter for the object is above a predefined threshold, which here is set to 0.7. Thus for representation 1021’, where the maximum correlation parameter is 0.9, a type of radiation source associated with the predefined sub-range(s) of energy (Eb) to which said correlation parameter relates, which here is the radioisotope Ba-133, is assigned as a label. For representation 1022’, where the maximum correlation parameter is 0.8, a type of radiation source associated with the predefined sub-range(s) of energy (Ec) to which said correlation parameter relates, which here is the radioisotope Cs-137, is assigned as a label. Thus representation 1021’ is assigned the label 1021C indicating ‘Ba-133’ and representation 1022’ is assigned the label 1022C indicating ‘Cs-137’. Representations 1023’ and 1024’, both of which are related to maximum correlation parameters of <0.7, are assigned respective ‘null’ labels 1023C and 1024C.

[0166] Exemplary labels indicating object type, correlation parameter, and radiation source type, in Figure 12, are textual. However, it will be appreciated any form of visual indicator can be used, which may or may not include text. For example, any of the labels may comprise a colour, brightness, shape, and / or a textual or other symbolic marker, having a predefined association with a value or identity to be indicated. Figure 12 further shows, schematically, a visual indicator associated with representations 1021’ and 1022’, comprising a hatched overlay, which here acts as a further indication that the maximum correlation parameter for each of these representations is above a predefined threshold value (here 0.7). It will be appreciated many other forms of visual indication could be used, such as bounding boxes placed around representations of objects inP131127GB

[0167] the scene 105, where the colour of the bounding box has a predefined mapping to a maximum correlation parameter value (i.e. a green-to-red heat-map may be applied where a correlation parameter value of 0 equates to green, and a correlation parameter value of 1 equates to 1). The visualisation data generator module 1906 is configured to label the image data for the time t2 with one or more of a object type labels, correlation degree labels, and radiation source type labels, and output the image data with the one or more labels to the visual display unit 191 for viewing by a user. As shown schematically in Figure 7, the visualisation data, comprising image data and associated labels, may be transmitted to a user output driver 1907 (e.g. comprising one or more graphics cards), for output to the visual display unit 191. The specific choice of labels to be used, and their form of visual representation (e.g. textual vs non-textual, choice of heat-maps, etc) may be configured by a user via a suitable menu arrangement configured for display on a user input interface (e.g. on visual display unit 191). Thus a user may be provided on visual display unit 191 with a visualisation of a scene 105’, as shown schematically in Figure 12, where the scene 105’ comprises image data containing representations of objects in a monitoring region 105 at a time t2, and at least one representation of at least one object in the scene 105’ is labelled with at least one object type labels, correlation degree label, and I or radiation source type label. The visualisation data may be displayed on the display 191 on a continuous basis, or may be retrieved from the storage medium 1909 and presented for display in response to a trigger provided by a user. Thus, for example, the visualisation data generator 1906 can be configured to store, for a plurality of sequential time points, a frame I still image corresponding to a view of the monitoring region 105 of the pedestrian radiation monitoring apparatus 1, at each time point, along with an object type label, and I or correlation degree label, and I or radiation source type label, for each of at least one objects represented in each frame I still image. These sequential time points may together span seconds, minutes, hours, days, months, or years, of clock time. A selection of a sub-span of time for which to present visualisation data comprising image(s) and label(s) on the visual display unit 191 , may made according to the preference of the skilled person, but by way of non-limiting examples, the following may be used:

[0168] • A user may input to the visualisation data generator 1906 of the radiation monitoring control logic 190 a specific period of time in the past for which they wish to retrieve visualisation data; and I or

[0169] • The analyser I MCA module 1902 may trigger an alarm when a count rate of radiation detected by at least one radiation detector (e.g. gamma radiation detector 100A) exceeds a predefined threshold (i.e. in terms of total count rate, or count rate for one or more subranges of energy), and based on triggering of the alarm, signal to the visualisation data generator 1906 to initiate display of visualisation data on the visual display unit 191,P131127GB

[0170] starting at the time when the alarm was triggered. A display of real-time or near-real-time visualisation data may continue until the analyser / MCA module 1902 detects the count rate of radiation detected by at least one radiation detector has fallen back below the threshold;

[0171] It will be appreciated that various modifications may be made to embodiments of the present disclosure without departing from the general approach. Significantly, which a gamma radiation detector 100A has been used herein as a particular type of radiation detector for the purposes of providing a concrete example of a type of radiation detector with which approaches according to the present disclosure can be applied, the skilled person will appreciate that all the approaches herein can be modified for use with any other form of radiation which can be detected by a suitable radiation detector. Thus, for example, references to a ‘gamma radiation detector 100A’ herein can be replaced with references to other forms of radiation detector, configured for detecting, for example, other forms of electromagnetic radiation, or particle radiation, or acoustic radiation. Such detectors are known to the skilled person, and it will be appreciated that while the specific MCA I analyser module configuration will be dependent on the type of detector, the principles herein of obtaining radiation data (e.g. in the form of a spectrum of radiation intensity with respect to energy or frequency) and obtaining intensity parameters for correlation with changes in spatial position of objects in a monitoring region of the detector, can be applied with relevant modifications.

[0172] Thus, for example, in embodiments of radiation monitoring apparatus for use with the approaches herein, where the radiation detector comprises a particle radiation detector configured for detecting alpha (a), beta (P), proton, or neutron radiation, the radiation data output by the MCA I analyser circuitry may be represented, as for the exemplary gamma radiation spectrum of Figures 5 and 10, in terms of a spectrum of detection rate (e.g. count rate) for each of different sub-ranges of detection energy across an overall detection range of the detector. The intensity parameter may be derived by integrating the detection rate with respect to the overall detection energy range of the detector, or over one or more sub-ranges of detection energy.

[0173] In embodiments of radiation monitoring apparatus for use with the approaches herein, where the radiation detector comprises an electromagnetic radiation detector comprising one or more of a radio detector configured for detecting radio wave radiation; a microwave detector configured for detecting microwave radiation; an infra-red (IR) detector configured for detecting IR radiation; a visible light detector configured for detecting radiation in the human-visible portion of the electromagnetic spectrum; an ultraviolet (UV) detector configured for detecting UV radiation; and an X-ray detector configured for detecting X-ray radiation; or a gravitational wave detector configured for detecting gravitational waves; the radiation data output by the MCA I analyser circuitry may be represented in the form of a spectrum of intensity (e.g. W / m2) for each of differentP131127GB

[0174] sub-ranges of detected frequency (hZ) across an overall detection range of the detector. The intensity parameter may be derived by integrating the intensity with respect to the overall detected frequency range of the detector, or over one or more sub-ranges of detected frequency.

[0175] In embodiments of radiation monitoring apparatus for use with the approaches herein, where the radiation detector comprises an acoustic radiation detector configured for detecting sound waves (e.g. ultrasound waves), the radiation data output by the MCA I analyser circuitry may be represented in the form of a spectrum of sound pressure level (dB) for each of different subranges of detected frequency (hZ) across an overall detection range of the detector. The intensity parameter may be derived by integrating the sound pressure level with respect to the overall detected frequency range of the detector, or over one or more sub-ranges of detected frequency. Where a radiation detector system 100 comprises plural detectors (e.g. a gamma radiation detector and a neutron radiation detector, as in the example of Figures 1, 2, and 4), whether or not these are configured to detect the same type of radiation, the correlation approaches herein may be applied separately (for example in parallel) for each radiation detector, and I or each type of detected radiation. Visualisation data labels indicative of a degree of correlation between spatial positon of objects and changes in radiation intensity parameter, and visualisation data labels indicative of a determined radiation source type for one or more objects, may be separately generated by the visualisation data generator module 1906 for each of a plurality of different types of detected radiation (e.g. for both of gamma radiation, based on radiation data from at least one gamma radiation detector, and neutron radiation, based on radiation data from at least one neutron radiation detector).

[0176] In so far as embodiments of the disclosure have been described as being implemented, at least in part, by software-controlled data processing apparatus, it will be appreciated that a non-transitory machine-readable medium carrying such software, such as an optical disk, a magnetic disk, semiconductor memory or the like, configured to carry out any of the approaches associated with the radiation monitoring control logic 190 herein, is also considered to represent an embodiment of the present disclosure.

[0177] It will be appreciated that the above description for clarity has described embodiments with reference to different functional units, circuitry and / or processors. However, it will be apparent that any suitable distribution of functionality between different functional units, circuitry and / or processors may be used without detracting from the embodiments.

[0178] Described embodiments may be implemented in any suitable form including hardware, software, firmware or any combination of these. Described embodiments may optionally be implemented at least partly as computer software running on one or more data processors and / or digital signalP131127GB

[0179] processors. The elements and components of any embodiment may be physically, functionally and logically implemented in any suitable way. Indeed, the functionality may be implemented in a single unit, in a plurality of units or as part of other functional units. As such, the disclosed embodiments may be implemented in a single unit or may be physically and functionally distributed between different units, circuitry and / or processors.

[0180] Although the present disclosure has been described in connection with some embodiments, it is not intended to be limited to the specific form set forth herein. Additionally, although a feature may appear to be described in connection with particular embodiments, one skilled in the art would recognize that various features of the described embodiments may be combined in any manner suitable to implement the technique.

[0181] Figure 13 is flow chart schematically showing steps of a method according to the present disclosure, to be implemented by control logic of a radiation monitoring apparatus, wherein the method comprises a step D1 of receiving radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; a step S2 of detecting a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation; a step S3 of determining, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of an intensity of radiation detected by the radiation detector; and a step S4 of correlating the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

[0182] REFERENCES

[0183] [1] GB patent GB 2463707

[0184] [2] GB patent GB 2504771

[0185] [3] EP patent EP3637150

[0186] [4] GB patent GB 2445578

Claims

P131127GBCLAIMS1. A radiation monitoring method comprising:receiving radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation; detecting a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation;determining, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of an intensity of radiation detected by the radiation detector; andcorrelating the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

2. The method of claim 1 , further comprising classifying at least one of the one or more objects as an emitter of radiation detected by the radiation detector, based on determining a degree of correlation between the detected change in spatial position of each object and the determined change in the radiation intensity parameter.

3. The method of claim 2, wherein classifying the at least one object as an emitter of radiation detected by the radiation detector comprises estimating a likelihood the object is an emitter of radiation.

4. The method of any preceding claim, further comprising receiving object position data generated by an object position sensing system;wherein the object position data is indicative of positioning of each of the one or more objects within a region from which the radiation detector is configured to receive radiation; and detecting the change in the spatial position of each object based on the object position data.

5. The method of claim 4, wherein the object position data is detected by at least one object position sensor distinct from the radiation sensor.

6. The method of any of claims 4 to 5, wherein the at least one object position sensor is configured to collect object position data from a plurality of different sensing locations.P131127GB7. The method of any of claims 4 to 6, wherein the object position sensing system comprises at least one of a satellite-based location sensing system, a light detection and ranging system, an acoustic ranging system, and a depth detection system.

8. The method of any of claims 4 to 7, wherein the object position sensing system comprises an imaging system configured to generate images representing the region from which the radiation detector is configured to receive radiation, wherein detecting the change in the spatial position of each of the one or more objects between the first time point and the second time point comprises:generating an image sequence comprising a first image of the object at the first time point and a second image of the object at the second time point; andprocessing the image sequence to detect the change in the spatial position of the object.

9. The method of claim 8, wherein the image sequence comprises a plurality of further images generated by the imaging system at sequential time points between the first time point and the second time point.

10. The method of any of claims 8 to 9, wherein processing the image sequence to detect the change in the spatial position of the object comprises applying a first trained classifier, preferably a neural network, to the image sequence and outputting from the second trained classifier an indication of the change in the spatial position of the object.

11. The method of any of claims 8 to 10, further comprising processing the image sequence by applying a second trained classifier, preferably a neural network, to the image sequence, and outputting from the second trained classifier an indication of an object type associated with each of the one or more objects.

12. The method of any preceding claim, wherein detecting the change in the spatial position of between the first time point and the second time point comprises determining a distance moved by the object between the first time point and second time point.

13. The method of claim 12, wherein the distance is a change in distance between the object and the radiation detector.

14. The method of any preceding claim, wherein the radiation intensity parameter is a first radiation intensity parameter indicative of a change in an intensity of radiation detected by the radiation detector associated with a first sub-range of detection energy from within an overall range of detection energy of the radiation detector, wherein the method further comprises:P131127GBdetermining, based on the radiation data, a change in a second radiation intensity parameter between the first time point and the second time point, wherein the second radiation intensity parameter is indicative of a change in an intensity of radiation detected by the radiation detector for a second sub-range of detection energy from within the overall range of detection energy of the radiation detector, the second sub-range being different to the first sub-range; and correlating the detected change in the spatial position of each of the one or more objects with the determined change in the second radiation intensity parameter.

15. The method of any preceding claim, further comprising:generating visualisation data comprising an image or video containing representations of each of the one or more objects; andassigning a first label to a representation of at least one object in the visualisation data; andoutputting the generated visualisation data with the first label for display;wherein the first label is assigned to the representation of the object based on a degree of correlation between the change in spatial position of the object and the change in the radiation intensity parameter.

16. The method of claim 15, wherein the first label comprises a colour, brightness, shape, and / or a textual or other symbolic marker, having a predefined association with the degree of correlation between the change in spatial position of the object and the change in the radiation intensity parameter.

17. The method of any of claims 15 to 16, comprising classifying radiation detected by the radiation detector by analysing the received radiation data to determine a characteristic of the radiation detected by the radiation detector, wherein the first label indicates the characteristic of the radiation.

18. The method of any of claims 15 to 17, comprising classifying radiation detected by the radiation detector by analysing the received radiation data to determine a type of radiation source associated with the radiation detected by the radiation detector, wherein the first label indicates the type of radiation source.

19. The method of claim 18, wherein the first label indicates a type of radiation emitting device.

20. The method of any preceding claim, wherein the radiation comprises nuclear radiation.P131127GB21. The method of any of claims 15 to 20, when dependent on claim 11, further comprising:assigning a second label to a representation of at least one object in the visualisation data, wherein the second label indicates an object type associated with the object; and outputting the generated visualisation data with the second label for display; wherein the second label is assigned to the representation of the object based on the output from the second trained classifier of the indication of the object type associated with the object.

22. The method of any of claims 20 to 21 , when dependent on claim 18, wherein the first label indicates a radioactive material, preferably a radioisotope, or a class of radioactive materials.

23. The method of claim 22, wherein determining a type of radiation source associated with the radiation detected by the radiation detector comprises analysing the received radiation data to determine a characteristic of the radiation corresponds to a predefined characteristic associated with at least one of:a class of special nuclear materials, SNM, and / or a specific member of said class; a class of naturally occurring radioactive materials, NORM, and / or a specific member of said class;a class of industrial radioactive materials, and / or a specific member of said class; and assigning a first label which indicates the class of materials, and I or specific member of said class, associated with the predefined characteristic determined to correspond to the characteristic of the radiation.

24. The method of any preceding claim, wherein the intensity parameter is based on a count rate of detection events by the radiation detector.

25. The method of any of claims 1 to 21, wherein the radiation comprises electromagnetic radiation.

26. The method of any of claims 1 to 21, wherein the radiation comprises acoustic radiation.

27. The method of any preceding claim, wherein the one or more objects comprise at least one pedestrian.P131127GB28. The method of any preceding claim, wherein the one or more objects comprise at least one vehicle.

29. The method of any preceding claim, wherein the one or more objects comprise at least one item of cargo or luggage.

30. The method of any preceding claim, wherein correlating the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter comprises weighting a radiation intensity parameter for at least one of the first and second time points, based on estimating a degree of radiation shielding provided by a shielding object disposed between the radiation detector and the object.

31. The method of claim 30, wherein estimating the degree of radiation shielding comprises:obtaining at least one image of the object and the shielding object at the one of the first and second time points; anddetermining from the at least one image that the shielding object overlaps the object with respect to a direction from the radiation detector towards the object.

32. The method of claim 31 , wherein estimating the degree of radiation shielding comprises estimating a degree to which a representation of the shielding object in the at least one image overlaps a representation of the object in the at least one image.

33. The method of any of claims 30 to 32, wherein estimating the degree of radiation shielding comprises determining a first solid angle subtended by the object from an evaluation location in or on the radiation detector.

34. The method of claim 33, wherein estimating the degree of radiation shielding comprises determining a second solid angle subtended by the shielding object from the evaluation location.

35. The method of any of claims 30 to 34, wherein estimating the degree of radiation shielding comprises applying a trained classifier, preferably a neural network, to the at least one image, outputting from the trained classifier an indication of a object type of the shielding object, and estimating the degree of radiation shielding based at least partly on the indication of the object type of the shielding object.P131127GB36. The method of any preceding claim, wherein correlating the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter comprises weighting a radiation intensity parameter for each of at least one of the first and second time points, based on a solid angle subtended by the radiation detector from an evaluation location in or on the object at each of the at least one of the first and second time points.

37. A non-transitory computer program product configured to control a computer to perform a method according to any preceding claim38. A recording medium storing a non-transitory computer program product according to claim 37.

39. Radiation monitoring circuitry comprising control logic configured to:receive radiation data generated by a radiation detector based on detection of radiation from a region from which the radiation detector is configured to receive radiation;detect a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector is configured to receive radiation;determine, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of an intensity of radiation detected by the radiation detector; andcorrelate the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

40. The radiation monitoring circuitry of claim 39, further configured to carry out the method of any of claims 2 to 36.

41. A radiation monitoring apparatus comprising the radiation monitoring circuitry of any of claims 39 to 40, further comprising the radiation detector.

42. The radiation monitoring apparatus of claim 41 , further comprising an object position sensing system configured to transmit object position data to the radiation monitoring circuitry, wherein the object position data is indicative of positioning of each of the one or more objects within the region from which the radiation detector is configured to receive radiation, wherein the control logic is configured to detect the change in the spatial position of each object based on the object position data.P131127GB43. Radiation monitoring circuitry means comprising control logic means configured to: receive radiation data generated by a radiation detector means based on detection of radiation from a region from which the radiation detector means is configured to receive radiation;detect a change, between a first time point and a second, subsequent time point, in a spatial position of one or more objects within the region from which the radiation detector means is configured to receive radiation;determine, based on the radiation data, a change in a radiation intensity parameter between the first time point and the second time point, the radiation intensity parameter being indicative of an intensity of radiation detected by the radiation detector means; and correlate the detected change in the spatial position of each of the one or more objects with the determined change in the radiation intensity parameter.

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