MARKSMANSHIP TRAINING SYSTEM PROVIDING PERFORMANCE MEASUREMENT FOR VARIABLE THREAT SCENARIOS

Description

CROSS REFERENCE TO RELATED APPLICATIONS

The present application claims priority under 35 U.S.C. 119 (e) to the provisional patent application filed on Oct. 8, 2024 and assigned application No. 63/704,579 (Attorney Docket 16921-002P). The contents of that application are incorporated herein.

FIELD OF THE INVENTION

The present invention relates to a system for marksmanship training that provides variable threat scenarios for multiple threats.

BACKGROUND OF THE INVENTION

Skills improvement is a result of diligent practice and objective performance measurement. Certain practice modalities prove more efficacious because they immerse the trainee in scenarios that more faithfully replicate operational conditions and incorporate a more comprehensive variety of skills. Once a practitioner has identified realistic methods to train, they need an efficient and effective technique for gathering feedback.

Performance measurement allows a practitioner to compete with themselves, celebrate improvements, and examine the factors that contributed to less than acceptable performance. Modern marksmanship training lacks the dynamic, feedback rich nature necessary to engage practitioners and help them to improve skills relevant to their self-defense or competitive abilities. An overwhelming majority of training consists of shooting at static paper targets while stationary. In order to gather enough data to identify trends from this type of training, a user must dedicate a disproportionate amount of time to manual notation and analysis. Even then, many important trends and data points will be missing due to the limitations of current training tools.

BRIEF DESCRIPTION OF THE DRAWINGS

Various objects, features and attendant advantages of the present invention will become fully appreciated as they become better understood when considered in conjunction with the accompanying drawings, in which like reference characters designate the same or similar parts throughout the several views, and wherein:

FIG. 1 illustrates a front view of a silhouette target constructed according to the present invention

FIG. 2 illustrates a rear view of the target of FIG. 1, depicting certain components associated with the present invention.

FIGS. 3-8 illustrate sequential steps and data transfers of the present invention for several different threat scenarios.

DETAILED DESCRIPTION OF THE INVENTION

High-end training facilities and shooting competitions incorporate shooter movement, manual accuracy assessment, and a form of time recording. Manual accuracy assessment is a time-consuming process requiring a person to go downrange to the target, mark the hit and notate the distance to the target center. Generally, the impact point is marked by crossing it with a pen/sharpie, putting a sticker over the impact point, or painting over the impact point.

These facilities often lack technology that provides versatile visual stimuli that requires a shooter to actively respond to one or more stimuli in the moment; nor do they have the ability to gather and record precise real time data about a shooter's marksmanship, situational awareness (e.g., response to varying and rapid threat changes), or ability to prioritize threats and based thereon seek to neutralize the threats according to a priority sequence.

Instead, these prior art techniques use an auditory “beep” to signal a shooter to begin shooting, depend on the shooter to have memorized a specific course of fire (COF), and to complete that COF. In firearms training, a course of fire (COF) is a set of actions that a shooter is intended to complete during a given drill or scenario. Important to note that because the COF has been committed to memory before a competitor's performance is measured, this arrangement has only the capability to measure action time, not reaction time. Reaction involves stimulus perception, processing, integration, motor planning and response execution, whereas action time is simply response execution.

Optimally, a shooter should be prompted by visual stimuli instead of relying on auditory cues and memory to complete a COF. The visual stimuli, as provided by the present invention, builds appropriate neural pathways for efficiently responding to visual indicators in future real-world self-defense scenarios. The present invention (commercially referred to as INSTINCT training platform) provides users with new degrees of performance measurement, trains users by presenting more realistic training scenarios and thereby rapidly improves the user's capabilities.

This system comprises three primary components: a mobile application executing on a smart phone or computer, sometimes referred to herein as a remote device, a threat indicator preferably mounted on a rear surface of a target (preferably a steel target), and a communications hub for relaying signals between the smart phone or computer executing the mobile application and the threat indicator. The smart phone or computer further comprises a human interface component (typically a display) for use in presenting performance and archived information to the user.

The system thus provides an affordable and novel technique to train for dynamic self-defense scenarios, consistently record insightful performance metrics, and compete with other users to progressively improve the shooter's skills.

Note that references to threat indicator and indicator are used interchangeably herein.

Threat level, threat status, and threat disposition are all references to the signals (colors) displayed by the threat indicator and represent the status of a specific threat. For example, the references in the explanations of various scenarios refer to a threat represented by a target, not the threat indicator, which is a physical component of the present invention.

The system of the present invention employs a training methodology wherein the system signals the user if and when to shoot at a given target, collects timestamps of hits to measure reaction time, collects accuracy data as to where the intended target was hit, and measures the shooter's threat prioritization (e.g., how well the shooter prioritizes the various threats presented, each having a different priority or threat level).

FIG. 1 illustrates a front surface of a target 10, sometimes referred to as a steel silhouette target and a light reflector 12 that bends or refracts light emitted from an LED toward the user. One or more LEDs or light pipes within the light reflector can display various colors, each color representing a different threat status. A user or shooter can see the color displayed by the light reflector and thereby determine the threat presented.

FIG. 1 also indicates a mobile device 15 (comprising a display 15A) and a communications hub 17. A communications link is depicted by double-headed arrowheads 18 representing radio frequency signals exchanged among a communications component (as further described below) mounted to the target 10, the communications hub 17, and the mobile device 15 where various performance metrics are calculated and stored. Typically, the hub 17 serves as a relay device, receiving signals from the mobile device 15 and transmitting them to the communications device mounted to the target 10 (and vice versa).

Several system components are attached to a rear surface of a fixed or moveable target 10 (preferred target form factors include silhouettes of a human figure, square, rectangular, and circular plates/gongs and preferred material for the target comprising steel). See FIG. 2. One embodiment includes a threat indicator 20, which comprises (not separately illustrated in FIG. 2 as these components are within the threat indicator housing or enclosure) a microcontroller, a GPS receiver, a battery, LED lights (for example, red, green, and blue, in one embodiment) for illuminating the light reflector 12 of FIG. 1, a wireless communications device (preferably a single chip), and a custom PCB for connecting these components. An antenna 22 transmits signals to and receives signals from the communications hub 17. The communications hub 17 serves as the communications interface between the threat indicator 20 and the mobile device 15.

Note that the threat indicator is disposed behind and protected by the target and the components of the threat indicator are disposed within a housing or enclosure.

Although certain components as described above are identified as attached to the rear surface of the target, in another embodiment those components provide the same functionality, but are not necessarily attached to the target. For example, the threat indicator may comprise a puck-shaped device with LED lights, microcontroller, battery, sensor (such as a microphone), and communications chip all disposed within the puck enclosure. The puck can be placed on the ground either directly in front of the user or within their peripheral vision. In conjunction with the intended use cases for the system, placement of the puck can be used to signal environmental changes. For example, in a military training scenario, puck-mounted LEDS may signal the necessity to retreat in the face of overwhelming threats.

With the placement of the threat indicator other than on the target, another use case is suggested with the use of paper targets. Several different colored paper targets (either different shapes/colors on the same paper target or different targets entirely) are used with the puck, which signals the next target the shooter needs to hit.

The steel target embodiment (FIGS. 1 and 2) includes the bullet-permeable light reflector 12 that controllably shines various light colors at different times according to scenario instructions; the light originating from the LEDS within the threat indicator and in one embodiment propagating through a light pipe 13 to the light reflector. The microcontroller within the threat indicator controls the LEDs and thus the timing and color output from the light reflector.

The system comprises a plurality of sensors 28 (connected to the threat indictor 20 via conductors 30, see FIG. 2) for determining the projectile point of impact. The threat indicator has seven ports (in one embodiment) five of the ports for connecting to one of five sensors, with the sensors providing inputs to the microcontroller within the threat indicator. Each sensor is separately physically attached to the target.

One of the two additional ports supplies power to the threat indicator and the seventh port carries a signal to the light reflector 12.

The system further comprises a shot sensor 31 for determining when a projectile was discharged from the shooter's weapon based on the sound associated with that discharge. The shot sensor bidirectionally communicates with the communications hub 17 and is located proximate to the shooter. According to another embodiment, the shoot sensor comprises a audio sensor (such as a microphone) at the communication hub. In yet other embodiments, the sensor is wearable (for example, on the user's wrist) or is mounted on the firearm.

The user programs the threat indicator(s) through a mobile application on the remote device 15 (such as a mobile phone) that serves as a system controller, a database, and a human interface device (HID) with the display 15A. The threat indicator(s) and the mobile application are connected through the communications hub 17. The hub's primary function is to relay radio communications signals between the user app and the threat indicator device(s), as described above, but the hub also serves as a shot timer (collecting the precise timestamps of shots from a given shooter based on the sound of their firearm's report).

FIG. 2 also includes targets 10A and 10B (each including all components of target 10, including reflectors 12A and 12B). Several of the scenarios (COFs) described herein involve multiple threats. Typically, each threat requires a target with components identical to those depicted with target 10. Thus, the additional targets 10A and 10B are for use with a scenario involving three threats, with the status of each threat indicated by the light color as displayed via the reflectors 12, 12A, and 12B.

One complexity that may arise in applications involving multiple shooters simultaneously relates to determining which shooter fired the projectile that struck a specific target. Preferably, to distinguish between multiple shooters the microphone in the remote device can be fine-tuned to distinguish higher decibel reports from a firearm that is closer to the microphone. Alternatively, this can be accomplished with an additional sensor attached to the firearm or user's wrist that indicates when the projectile was fired. However, in most situations, safety considerations dictate that only one shooter uses a tactical range at any given time.

Multiple targets outfitted with these threat indicator devices can be used in concert to simulate a wide variety of scenarios depicted in FIGS. 3-8. All communications and coordination of the indicator light(s) and sequences are determined through the user-programmed mobile app. Note the scenario of FIG. 5 relates to only a single threat.

Light sequences (from differently colored LEDs) indicate, when illuminated, the disposition (threat level) that a target represents at that time. For example, an illuminated red LED may indicate a lethal threat, yellow a non-lethal threat, and green a non-threat. Certain scenarios also include a threat behind a hard cover, which may be represented by a blue light, for example.

The various scenarios that can be provided by the system can be used to practice appropriate escalation and de-escalation of force in self-defense and law enforcement training programs. See FIG. 4 further described below.

For military training, blue may represent a target protected behind a cover, allowing the device to simulate time-sensitive shot opportunities by switching from red to blue and back, to indicate, by a red light, when a target is exposed. See FIG. 3 further described below.

In a simple drill scenario, such as training drills or testing visual reaction time, a light will display a designated color to indicate a present lethal threat, the shooter will fire rounds until the shooter reaches the programmed/designated number of hits, and the exercise is over.

The threat indicator uses a sensor array to identify the time and location of each projectile impact on the target. The sensors measure vibrations in the material/steel of the target. These timestamps are then compiled and sent to the mobile application where the location of the impact is calculated via time-of-flight (ToF).

Light activation timestamps (i.e., when the light was illuminated) and hit impulse timestamps (i.e., when the projectile hit the target) are sent via the radio communications hub to the mobile app. The mobile app then calculates the response time of the user (that is, the time elapsed between illumination of an LED/light reflector and the projectile striking the target), distance to the target, and location of the projectile impact on the target. Distance to the target is estimated by using GPS receivers in the user's phone and on the threat indicator.

The hit impulse sensors 28 of FIG. 2 allow for precise mapping of the location where the projectile hit the target since each sensor determines the impact at a different time based on the distance between the point of impact and the sensor. Analyzing the time of impact at each sensor and knowing the location of each sensor allows calculation of the point of impact. Sensors are positioned at the edges/corners of the target to maximize the accuracy of the ToF (i.e., maximizing the length of time between four synchronized timestamps/events, one timestamp supplied by each of four sensors) calculations and location of the point of impact.

Time split data is also useful to determine a user's reaction and action speeds. For example, by determining the number of rounds in each magazine at the start of the COF, the system can measure elapsed time to reload or elapsed transition time between the user terminating firing of their primary weapon (rifle) and beginning to fire with their secondary weapon (handgun).

The mobile app also provides the ability to record malfunctions (via user input) so that this data can be tracked. Malfunction data can help identify issues with an individual's shooting form or problems with the function of their firearm and thereby prevent future malfunctions.

The mobile app also provides a streamlined way to track maintenance schedules by accumulating round count and time elapsed between cleanings or part replacements. These data points will maximize the likelihood that a user's firearms are functioning optimally.

After the user chooses a COF or scenario on the mobile app, the settings (colors to display on each threat indicator and timing and sequence of the displayed colors) are transmitted from the remote device to the communication hub 17 and then to each threat indicator 20.

When the COF begins, the threat indicator turns specific color LED lights on/off at the programmed times based on instructions that define the COF. The shooter stands-by to receive a visual and/or audible stimulus, signaling him/her to assess and engage targets. Auditory stimuli can originate from the communication hub or the mobile application, including scenario specific audio (like gunshots in the distance or a victim screaming in distress). These audio events are sensed by the shot sensor 31 and timestamps of the events transmitted to the communications hub for relaying to the threat indicator 20 and/or the mobile device 15.

When a hit event is identified by the sensors operating in conjunction with the microcontroller/microprocessor of the threat indicator, the indicator transmits the device's unique identifier, GPS location of the indicator and precise timestamps from the hit impulse sensors to the communication hub and then in turn to the mobile application. This data is captured by the mobile app and used to calculate a variety of performance metrics, as further described herein.

The system can be programmed in four primary modes: scheduled, conditional, manual, and randomized. In this context, a scheduled program refers to COFs that follow a time-based set of instructions based on predetermined time queues. For an example of a scheduled drill, please refer to FIG. 3. Conditional COFs in contrast, are triggered by user actions as opposed to time-based transitions. An example of a conditional COF is depicted in FIG. 4. Once the pre-set requirements for a target are met in this type of programming (i.e. location or the shooter or number of hits or accuracy of a given hit), the communications hub signals the threat indicator(s) to present the next stimuli/stimulus.

Manual programming allows the trainer or instructor to adjust the scenario in near real-time. See FIG. 5. This is particularly useful for training appropriate use-of-force, as it allows the instructor to correlate the scenario to the trainee's perceived effectiveness in de-escalating the scenario.

Randomized COFs stress the importance of awareness because the user has no idea what to expect. They also allow for rapid revision of a given arrangement of targets. For example, in FIG. 7, a user programs the training device for a dynamic threat scenario. Then employs a randomize function to scramble the threat dispositions so a new COF is created without any additional setup time.

By using multiple threat indicators, the system can also train and measure a shooter's awareness, threat assessment, and prioritization of the various threats Factors like distance to a given threat can be used to train proper threat prioritization (addressing closer, more immediate threats before farther ones). See FIG. 7. Users can also test their perception of dynamic environments where threats may not readily present themselves. In FIG. 3, a training scenario is illustrated where a non-threat target develops into a lethal threat while the shooter is distracted by other lethal threats.

The GPS component provides time synchronization between clocks on different devices so that all the collected data is synchronized and precise to at least a millisecond scale. In addition, the GPS component provides data about the distance between the shooter and the target for each shot timestamp. This GPS data can be used to verify the comparability of a shooter's COF from different scenarios/arrangements. In other words, shooters who are using the same light sequence programs with targets that are the same form factor and size, at approximately the same distance will be able to compare their scores and thereby compete for the best score.

The mobile app also collects data regarding the weather (wind, precipitation, visibility, humidity, barometric pressure, and altitude) as relevant data points that could impact a shooter's score. Weather data will be pulled through online APIs that access a weather database. If mobile/cellular data is not available (to access these APIs), the app can retroactively add the weather data based on location timestamps once connectivity to the weather app is available.

Another advantage of using GPS in this system is that it enables movement drills and courses of fire that have conditional location-based triggers. The system provides a scenario where the user establishes geofences so that once a shooter enters the geofence, the system signals the threat indicator(s) visible from that spot to start the portion of the COF that is intended to occur in that designated area.

The system also enables the use of scenario-specific auditory cues to simulate realistic events. For example, the mobile app/phone could play sounds of an active shooter or a person in distress to signal the user to respond. These sounds could be played through the phone's speaker, via the communication hub, or, if the user has electronic audio-enabled hearing protection, the sounds can be played directly through the speakers of the hearing protection (ear buds or ear muffs).

Another scenario comprises a user or shooter responding to audio of a nearby person in distress and must move to multiple locations to identify the threat(s). In this scenario, threat dispositions change dynamically based on the shooter's actions and movements. Scenarios like this provide exemplary means for law enforcement to practice and assess de-escalation and appropriate use of force.

The mobile application serves as the primary storage device for all shooter data. Data can then be uploaded to a database where users can compare their scores on mobile and web-based displays. This feature democratizes the shooting competition market and fosters competition between friends and rivals, regardless of their geographic proximity.

The categories of competition can be divided into various metrics, scenarios, and degrees of verification. Users and training ranges that verify the size, form factor and distance to targets and indicators will be able to access top-tier competition categories. Simple measurements like reaction time or draw-to-hit time will be in the lower category tiers as they require less verification compared to multi-target sequences with varied target distances. Scores in certain standardized categories are comparable between users in online leaderboards.

By automatically collecting and aggregating this data, the system of the present invention creates a much faster feedback loop for providing results to the users, as well as long term data archives, and organization of the data for visualizing trends.

The raw timestamps from the threat indicators can be used to calculate a wide variety of performance metrics. These metrics (reaction time, accuracy, threat assessment, target acquisition, reload speed, weapon transition speed, etc.) can be used to create a more objective measure of a shooter's capability. Each performance measurement can be correlated to a specific skill category, that impacts the user's rating.

Generally, the five skill categories are accuracy, dexterity, urgency, movement, and awareness. To elaborate on what each of these skill categories entail, examples are as follows.

Accuracy deals with how close to the optimal region of the target (often the center) the projectile impacts. This is also augmented by the distance between the shooter and the target, naturally shots that involve a greater distance require more skill to maintain accuracy.

Dexterity refers to how quickly a user performs tasks like reloading or dealing with malfunctions.

Urgency involves the speed of actions, such as draw time from a holster, weapon transitions and follow-up shots.

Movement incorporates insights on a user's speed of locomotion, use of cover/concealment and ability to shoot effectively while moving.

Finally and most importantly, awareness measures how attentive a user is to changes in their environment, particularly imminent threats.

Not all courses of fire involve all five skill categories. Some COFs yield specialized metrics that can only be captured via the requirements for that specific drill. A drill is a subset or an element of a COF. All drills can be considered a course of fire. As a course of fire grows in complexity it may be more accurately referred to as a scenario. Transitioning from a primary weapon to a secondary weapon is a drill that, when performed, yields a specialized metric called weapon transition time.

Advantageously, the mobile app can use the stored data and calculations based thereon to identify patterns and areas of improvement for a user. These insights can be leveraged by recommending training drills that help a user address those gaps and optimize their proficiency.

One example of a calculated metric is revealed by completing a “shooting while moving drill”. In this drill a user will shoot at a target while walking. Three important metrics are involved here, accuracy, time, and speed of movement. Accuracy points (measured by IPSC/International Practical Shooting Confederation standards) are divided by total time, yielding hit factor. The hit factor is then multiplied by average movement speed (miles per hour) to yield a holistic performance measurement. In equation format: “MPH (accuracy points/total time)=Shooting While Moving Score”.

FIG. 7 depicts instruction and data flow sequential steps for a scenario related to threat assessment and prioritization. FIG. 7 also shows data flow to and from the mobile app in the leftmost column and functions at the communications hub in the second from the far left column.

In this threat scenario, the user encounters three targets (T1, T2 and T3) at different distances from the user. The scenario is designed to assess a shooter's ability to identify the most dangerous threats and efficiently prioritize them. In addition, this drill requires the user to be aware of changes in the environment because T1 is initially a non-threat, but develops into a lethal threat while the user is distracted by lethal threats T2 and T3.

As the shooter begins the scenario, they will notice that there are two targets displaying red (to indicate a lethal threat), one at a distance of 30 (T3) yards and one at 50 yards (T2). The shooter will also notice T1 at 40 yards displays green to indicate a non-threat status. Because closer threats are inherently more dangerous, the shooter is expected to hit T3 at 30 yards first, then T2 2 at 50 yards.

When the T3 has been hit the associated LED is turned off, time of impact is recorded and this data is sent to the mobile app. Also, the non-threat target indicator for the T1 changes to yellow to indicate a hostile reaction. The shooter then fires at T2 at 50 yards and hits the target.

Once the target at 50 yards (T2) has been hit, the target indicator T1 changes to red to simulate this individual presenting/using a weapon in a hostile manner. The user is then expected to hit T1.

The scenario is scored according to how well the user prioritizes the threats, how quickly and accurately they shoot at each target, and their response time to the dynamic threat at 40 yards.

As shown, the mobile app receives the relevant data (timestamps and GPS information) and performs the necessary calculations to score the performance. The app can also recommend additional drills to improve the shooter's score.

After completing the drill described above, users may want to randomize the settings of the drill to provide a fresh COF without any manual reconditioning (moving targets, adjusting settings in the app, etc.). FIG. 8 depicts a variant of the former drill with new stimuli and requirements. In this new version of the drill the first lethal threat (T1) requires 2 hits on target before the threat is eliminated. After addressing the first threat, a new threat (T2) arises and is hit. Finally, T2 changes from non-threat (green), to non-lethal threat (yellow) to deadly threat (red) and is hit by the user.

FIG. 3 depicts instruction and data flow sequential steps for a scenario related to threats behind a cover. FIG. 3 also shows data flow to and from the mobile app in the leftmost column and data to and from the communications hub in the second column from the left.

The user is presented with time sensitive shots for T2 as indicated with the associated LED is red. The shooter must time the shots to impact while the indicator is red and if the target sensors indicate a hit, the target is neutralized. Note that hits registered while an LED indicator shows blue, will not be considered for completing the COF because they represent a protected target. This provides the opportunity for the shooter to practice using a cover while shooting and dealing with threats that use cover as well.

Target 2 initially is exposed (not behind cover) for 8 seconds (red), then moves behind cover for 15 seconds (blue) and presents a threat again for 8 seconds (LED red). During the last threat interval the target is hit.

T1 was initially behind a cover as indicated by the blue LED. But after 15 seconds T1 becomes a threat (red LED) for 8 seconds. T1 is hit prior to hitting T2.

Note that both LEDs are turned off after the associated target is hit.

The system records the time of impact (timestamps) for both T1 and T2 and sends that data to the mobile application via the communications hub.

FIG. 4 represents a conditional hostage and de-escalation scenario involving five targets T1 through T5. T1 and T2 are positioned at or near location 1 while T3, T4, and T5 are positioned at or near location 2. This scenario tests the user's ability to identify, react, and readjust their actions to leverage the most appropriate degree of force in the moment.

As in the prior scenarios, the user opens the mobile application, selects a course of fire, and presses the start button. The mobile application sends the programmed light sequence to the communications hub from where it is then sent to the threat indicators T1 through T5. The mobile application also plays audio of a hostage/abductee in distress in the distance, signaling the user to begin.

The user moves from start point to location 1 to begin the course of fire. Now the hub directs threat indicator 1 to initiate the location 1 light sequence, in which case both T1 and T2 are indicated with green LEDs meaning they represent non-threats (civilians in this case). The user recognizes there is no threat present at location 1 and continues moving to location 2. Once the user enters the geofence for location 2, the next set of instructions are initiated. The communications hub directs threat indicators T3, T4, and T5 to initiate the programmed light sequence, that is, T3 is shown as lethal according to a red LED, T5 is also indicated by a red LED. Threat indicator T4 displays a green LED indicating a friendly person, perhaps a hostage.

The user then hits and neutralizes T3 with 2 shots. The associated light is turned off and the threat indicator sends the relevant timestamps to the communications hub.

After T3 is hit that data is sent to the communications hub after which instructions are sent to turn the LED associated with T5 yellow, indicating T5 is now a non lethal threat, presumably because T5 is surrendering their weapon. This is an important test to determine if the user is actively responding to changes in threat disposition. If the user shoots T5 after the LED color has changed to yellow, then this may be recorded as a penalty to the user's score for the drill. At this point T4 is no longer a hostage as both captors have been neutralized.

Finally, as indicated in the far left column, the timestamps and GPS information are sent to the application on the remote device and metrics related to the user are calculated and archived.

The user can then repeat this drill or select a new drill after which the new lighting sequence associated with that drill begins.

Another example of a de-escalation drill is presented in FIG. 5 where an instructor is manually adjusting the threat disposition displayed by the indicator. In this example, the instructor feels that the trainee is not effectively de-escalating the scenario (by role playing a conversation to help the simulated threat calm down), so the instructor changes the disposition to (red) lethal threat. The trainee is then required to hit the target. The same compilation and calculation is performed by the mobile application, once all data is received from the indicators.

FIG. 5 presents a manual de-escalation scenario. The instructor initially sets the threat T1 to yellow indicating a potential threat, typically an agitated suspect. Upon determining that the trainee is not de-escalating the situation, the instructor then sets the target to red level indicating a lethal threat The user then hits the target, after which data (timestamps and GPS data) is compiled and sent to the remote device for calculating performance metrics and archiving the data.

FIG. 6 depicts a conditional dynamic threat involving threats T1, T2, and T3 each one positioned a different distance from the shooter, as indicated in FIG. 6. As with all other scenarios, the user opens the mobile application, selects the specific course of fire, and presses a start icon. The mobile application then sends the course of fire instructions to the communications hub, which then in turn sends the instructions to the affected threat indicators.

As indicated in FIG. 6, T1 is identified as a lethal threat while T2 and T3 are indicated as non lethal threats (green LED). The user hits and strikes threat T1 which results in data compilation and turns the T1 LED off.

The next set of instructions sent to the threat indicator, turning T2 to red while maintaining T3 at a green. The user then hits T2 after two misses (×3 reference in the Figure) and the LED is turned off and again data is compiled and sent to the mobile application.

T3 remains a non lethal threat with the display of a green light.

As with the other scenarios the timestamp information and GPS data are used to calculate performance metrics that are displayed on the remote device. The user can then select a new drill or repeat the prior drill and the process begins again.

Although the embodiments described herein refer to a visible light for indicating a threat, another embodiment includes a speaker for producing audio sounds that represent or indicate a threat.